Overview

Brought to you by YData

Dataset statistics

Number of variables114
Number of observations10676
Missing cells883786
Missing cells (%)72.6%
Duplicate rows23
Duplicate rows (%)0.2%
Total size in memory61.2 MiB
Average record size in memory5.9 KiB

Variable types

Text78
Categorical29
DateTime1
Numeric2
Unsupported4

Alerts

Violation Description - 23 has constant value "*28 Date marking > 24 hrs,on site,temp 41F" Constant
Violation Points - 23 has constant value "2.0" Constant
Violation Detail - 23 has constant value "228.75 Food. Time and temperature control. (g) Ready-to-eat, TCS food, date marking. (2) Except as specified in paragraphs (5) - (7) of this subsection, refrigerated, ready-to-eat, time/temperature controlled for safety food prepared and packaged by a food processing plant shall be clearly marked, at the time the original container is opened in a food establishment and held at a temperature of 41 degrees Fahrenheit (5 degrees Celsius) or less if the food is held for more than 24 hours, to indicate the date or day by which the food shall be consumed on the premises, sold, or discarded, based on the temperature and time combinations specified in paragraph (1) of this subsection: (A) the day the original container is opened in the food establishment shall be counted as day 1; and" Constant
Violation Memo - 23 has constant value "clearly date mark TCS food for 7 days only" Constant
Violation Description - 24 has constant value "*45 Drying Mops-air dry" Constant
Violation Points - 24 has constant value "1.0" Constant
Violation Detail - 24 has constant value "228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (f) Drying mops. After use, mops shall be placed in a position that allows them to air-dry without soiling walls, equipment, or supplies." Constant
Violation Memo - 24 has constant value "mops need dry" Constant
Dataset has 23 (0.2%) duplicate rowsDuplicates
Inspection Month is highly overall correlated with Inspection YearHigh correlation
Inspection Score is highly overall correlated with Violation Points - 22High correlation
Inspection Type is highly overall correlated with Violation Points - 19 and 3 other fieldsHigh correlation
Inspection Year is highly overall correlated with Inspection Month and 1 other fieldsHigh correlation
Street Direction is highly overall correlated with Violation Points - 20 and 2 other fieldsHigh correlation
Street Number is highly overall correlated with Violation Points - 20 and 2 other fieldsHigh correlation
Street Type is highly overall correlated with Violation Points - 22High correlation
Violation Points - 1 is highly overall correlated with Violation Points - 20 and 1 other fieldsHigh correlation
Violation Points - 10 is highly overall correlated with Violation Points - 22High correlation
Violation Points - 11 is highly overall correlated with Violation Points - 22High correlation
Violation Points - 12 is highly overall correlated with Violation Points - 22High correlation
Violation Points - 13 is highly overall correlated with Violation Points - 22High correlation
Violation Points - 15 is highly overall correlated with Violation Points - 19High correlation
Violation Points - 16 is highly overall correlated with Violation Points - 22High correlation
Violation Points - 17 is highly overall correlated with Violation Points - 19High correlation
Violation Points - 18 is highly overall correlated with Violation Points - 20 and 2 other fieldsHigh correlation
Violation Points - 19 is highly overall correlated with Inspection Type and 4 other fieldsHigh correlation
Violation Points - 2 is highly overall correlated with Violation Points - 20 and 2 other fieldsHigh correlation
Violation Points - 20 is highly overall correlated with Inspection Type and 9 other fieldsHigh correlation
Violation Points - 21 is highly overall correlated with Inspection Type and 9 other fieldsHigh correlation
Violation Points - 22 is highly overall correlated with Inspection Score and 13 other fieldsHigh correlation
Violation Points - 3 is highly overall correlated with Violation Points - 19 and 2 other fieldsHigh correlation
Violation Points - 4 is highly overall correlated with Violation Points - 20 and 2 other fieldsHigh correlation
Violation Points - 5 is highly overall correlated with Violation Points - 20High correlation
Violation Points - 7 is highly overall correlated with Violation Points - 21High correlation
Violation Points - 9 is highly overall correlated with Violation Points - 18High correlation
Inspection Type is highly imbalanced (91.8%) Imbalance
Street Direction has 6947 (65.1%) missing values Missing
Street Type has 220 (2.1%) missing values Missing
Street Unit has 6941 (65.0%) missing values Missing
Violation Description - 1 has 1002 (9.4%) missing values Missing
Violation Points - 1 has 1002 (9.4%) missing values Missing
Violation Detail - 1 has 1085 (10.2%) missing values Missing
Violation Memo - 1 has 2023 (18.9%) missing values Missing
Violation Description - 2 has 2108 (19.7%) missing values Missing
Violation Points - 2 has 2108 (19.7%) missing values Missing
Violation Detail - 2 has 2205 (20.7%) missing values Missing
Violation Memo - 2 has 3187 (29.9%) missing values Missing
Violation Description - 3 has 3384 (31.7%) missing values Missing
Violation Points - 3 has 3384 (31.7%) missing values Missing
Violation Detail - 3 has 3504 (32.8%) missing values Missing
Violation Memo - 3 has 4346 (40.7%) missing values Missing
Violation Description - 4 has 4643 (43.5%) missing values Missing
Violation Points - 4 has 4643 (43.5%) missing values Missing
Violation Detail - 4 has 4771 (44.7%) missing values Missing
Violation Memo - 4 has 5422 (50.8%) missing values Missing
Violation Description - 5 has 5815 (54.5%) missing values Missing
Violation Points - 5 has 5815 (54.5%) missing values Missing
Violation Detail - 5 has 5917 (55.4%) missing values Missing
Violation Memo - 5 has 6413 (60.1%) missing values Missing
Violation Description - 6 has 6794 (63.6%) missing values Missing
Violation Points - 6 has 6794 (63.6%) missing values Missing
Violation Detail - 6 has 6872 (64.4%) missing values Missing
Violation Memo - 6 has 7264 (68.0%) missing values Missing
Violation Description - 7 has 7608 (71.3%) missing values Missing
Violation Points - 7 has 7608 (71.3%) missing values Missing
Violation Detail - 7 has 7688 (72.0%) missing values Missing
Violation Memo - 7 has 7988 (74.8%) missing values Missing
Violation Description - 8 has 8311 (77.8%) missing values Missing
Violation Points - 8 has 8311 (77.8%) missing values Missing
Violation Detail - 8 has 8372 (78.4%) missing values Missing
Violation Memo - 8 has 8582 (80.4%) missing values Missing
Violation Description - 9 has 8871 (83.1%) missing values Missing
Violation Points - 9 has 8871 (83.1%) missing values Missing
Violation Detail - 9 has 8917 (83.5%) missing values Missing
Violation Memo - 9 has 9077 (85.0%) missing values Missing
Violation Description - 10 has 9368 (87.7%) missing values Missing
Violation Points - 10 has 9368 (87.7%) missing values Missing
Violation Detail - 10 has 9394 (88.0%) missing values Missing
Violation Memo - 10 has 9509 (89.1%) missing values Missing
Violation Description - 11 has 9767 (91.5%) missing values Missing
Violation Points - 11 has 9767 (91.5%) missing values Missing
Violation Detail - 11 has 9790 (91.7%) missing values Missing
Violation Memo - 11 has 9860 (92.4%) missing values Missing
Violation Description - 12 has 10098 (94.6%) missing values Missing
Violation Points - 12 has 10098 (94.6%) missing values Missing
Violation Detail - 12 has 10119 (94.8%) missing values Missing
Violation Memo - 12 has 10147 (95.0%) missing values Missing
Violation Description - 13 has 10329 (96.7%) missing values Missing
Violation Points - 13 has 10329 (96.7%) missing values Missing
Violation Detail - 13 has 10345 (96.9%) missing values Missing
Violation Memo - 13 has 10350 (96.9%) missing values Missing
Violation Description - 14 has 10467 (98.0%) missing values Missing
Violation Points - 14 has 10467 (98.0%) missing values Missing
Violation Detail - 14 has 10472 (98.1%) missing values Missing
Violation Memo - 14 has 10480 (98.2%) missing values Missing
Violation Description - 15 has 10532 (98.7%) missing values Missing
Violation Points - 15 has 10532 (98.7%) missing values Missing
Violation Detail - 15 has 10536 (98.7%) missing values Missing
Violation Memo - 15 has 10545 (98.8%) missing values Missing
Violation Description - 16 has 10592 (99.2%) missing values Missing
Violation Points - 16 has 10592 (99.2%) missing values Missing
Violation Detail - 16 has 10598 (99.3%) missing values Missing
Violation Memo - 16 has 10600 (99.3%) missing values Missing
Violation Description - 17 has 10629 (99.6%) missing values Missing
Violation Points - 17 has 10629 (99.6%) missing values Missing
Violation Detail - 17 has 10631 (99.6%) missing values Missing
Violation Memo - 17 has 10630 (99.6%) missing values Missing
Violation Description - 18 has 10651 (99.8%) missing values Missing
Violation Points - 18 has 10651 (99.8%) missing values Missing
Violation Detail - 18 has 10652 (99.8%) missing values Missing
Violation Memo - 18 has 10653 (99.8%) missing values Missing
Violation Description - 19 has 10661 (99.9%) missing values Missing
Violation Points - 19 has 10661 (99.9%) missing values Missing
Violation Detail - 19 has 10661 (99.9%) missing values Missing
Violation Memo - 19 has 10662 (99.9%) missing values Missing
Violation Description - 20 has 10669 (99.9%) missing values Missing
Violation Points - 20 has 10669 (99.9%) missing values Missing
Violation Detail - 20 has 10670 (99.9%) missing values Missing
Violation Memo - 20 has 10669 (99.9%) missing values Missing
Violation Description - 21 has 10669 (99.9%) missing values Missing
Violation Points - 21 has 10669 (99.9%) missing values Missing
Violation Detail - 21 has 10670 (99.9%) missing values Missing
Violation Memo - 21 has 10670 (99.9%) missing values Missing
Violation Description - 22 has 10673 (> 99.9%) missing values Missing
Violation Points - 22 has 10673 (> 99.9%) missing values Missing
Violation Detail - 22 has 10673 (> 99.9%) missing values Missing
Violation Memo - 22 has 10673 (> 99.9%) missing values Missing
Violation Description - 23 has 10675 (> 99.9%) missing values Missing
Violation Points - 23 has 10675 (> 99.9%) missing values Missing
Violation Detail - 23 has 10675 (> 99.9%) missing values Missing
Violation Memo - 23 has 10675 (> 99.9%) missing values Missing
Violation Description - 24 has 10675 (> 99.9%) missing values Missing
Violation Points - 24 has 10675 (> 99.9%) missing values Missing
Violation Detail - 24 has 10675 (> 99.9%) missing values Missing
Violation Memo - 24 has 10675 (> 99.9%) missing values Missing
Violation Description - 25 has 10676 (100.0%) missing values Missing
Violation Points - 25 has 10676 (100.0%) missing values Missing
Violation Detail - 25 has 10676 (100.0%) missing values Missing
Violation Memo - 25 has 10676 (100.0%) missing values Missing
Violation Description - 25 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Violation Points - 25 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Violation Detail - 25 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Violation Memo - 25 is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2025-04-14 23:23:19.813059
Analysis finished2025-04-14 23:23:42.380457
Duration22.57 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Distinct6072
Distinct (%)56.9%
Missing0
Missing (%)0.0%
Memory size797.6 KiB
2025-04-14T23:23:42.678074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length65
Median length51
Mean length19.480049
Min length3

Characters and Unicode

Total characters207969
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3180 ?
Unique (%)29.8%

Sample

1st rowBLUE'S PALACE II
2nd rowJFE SUSHI K-511
3rd rowDL MACK'S PRESTON
4th rowTHE POTTER'S HOUSE YOUTH ADDITION
5th rowMCDONALDS #4777
ValueCountFrequency (%)
1046
 
3.1%
the 432
 
1.3%
bar 396
 
1.2%
restaurant 390
 
1.1%
la 379
 
1.1%
kitchen 377
 
1.1%
food 363
 
1.1%
cafe 339
 
1.0%
el 325
 
1.0%
school 315
 
0.9%
Other values (5648) 29620
87.2%
2025-04-14T23:23:43.153813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23394
 
11.2%
E 18245
 
8.8%
A 18084
 
8.7%
R 12735
 
6.1%
O 12401
 
6.0%
S 11519
 
5.5%
I 11450
 
5.5%
T 11344
 
5.5%
L 10261
 
4.9%
N 10130
 
4.9%
Other values (58) 68406
32.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 207969
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
23394
 
11.2%
E 18245
 
8.8%
A 18084
 
8.7%
R 12735
 
6.1%
O 12401
 
6.0%
S 11519
 
5.5%
I 11450
 
5.5%
T 11344
 
5.5%
L 10261
 
4.9%
N 10130
 
4.9%
Other values (58) 68406
32.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 207969
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
23394
 
11.2%
E 18245
 
8.8%
A 18084
 
8.7%
R 12735
 
6.1%
O 12401
 
6.0%
S 11519
 
5.5%
I 11450
 
5.5%
T 11344
 
5.5%
L 10261
 
4.9%
N 10130
 
4.9%
Other values (58) 68406
32.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 207969
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
23394
 
11.2%
E 18245
 
8.8%
A 18084
 
8.7%
R 12735
 
6.1%
O 12401
 
6.0%
S 11519
 
5.5%
I 11450
 
5.5%
T 11344
 
5.5%
L 10261
 
4.9%
N 10130
 
4.9%
Other values (58) 68406
32.9%

Inspection Type
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size667.6 KiB
Routine
10568 
Follow-up
 
108

Length

Max length9
Median length7
Mean length7.0202323
Min length7

Characters and Unicode

Total characters74948
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRoutine
2nd rowRoutine
3rd rowRoutine
4th rowRoutine
5th rowRoutine

Common Values

ValueCountFrequency (%)
Routine 10568
99.0%
Follow-up 108
 
1.0%

Length

2025-04-14T23:23:43.278213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:23:43.345455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
routine 10568
99.0%
follow-up 108
 
1.0%

Most occurring characters

ValueCountFrequency (%)
o 10784
14.4%
u 10676
14.2%
R 10568
14.1%
t 10568
14.1%
i 10568
14.1%
n 10568
14.1%
e 10568
14.1%
l 216
 
0.3%
F 108
 
0.1%
w 108
 
0.1%
Other values (2) 216
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 74948
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 10784
14.4%
u 10676
14.2%
R 10568
14.1%
t 10568
14.1%
i 10568
14.1%
n 10568
14.1%
e 10568
14.1%
l 216
 
0.3%
F 108
 
0.1%
w 108
 
0.1%
Other values (2) 216
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 74948
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 10784
14.4%
u 10676
14.2%
R 10568
14.1%
t 10568
14.1%
i 10568
14.1%
n 10568
14.1%
e 10568
14.1%
l 216
 
0.3%
F 108
 
0.1%
w 108
 
0.1%
Other values (2) 216
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 74948
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 10784
14.4%
u 10676
14.2%
R 10568
14.1%
t 10568
14.1%
i 10568
14.1%
n 10568
14.1%
e 10568
14.1%
l 216
 
0.3%
F 108
 
0.1%
w 108
 
0.1%
Other values (2) 216
 
0.3%
Distinct388
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size83.5 KiB
Minimum2023-01-03 00:00:00
Maximum2024-02-29 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-04-14T23:23:43.435599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-14T23:23:43.573929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Inspection Score
Real number (ℝ)

High correlation 

Distinct46
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.707287
Minimum-26
Maximum100
Zeros0
Zeros (%)0.0%
Negative6
Negative (%)0.1%
Memory size83.5 KiB
2025-04-14T23:23:43.715359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-26
5-th percentile80
Q188
median93
Q397
95-th percentile100
Maximum100
Range126
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.9097106
Coefficient of variation (CV)0.075345273
Kurtosis28.474887
Mean91.707287
Median Absolute Deviation (MAD)4
Skewness-2.6141917
Sum979067
Variance47.744101
MonotonicityNot monotonic
2025-04-14T23:23:43.841151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
100 1001
 
9.4%
95 797
 
7.5%
97 744
 
7.0%
96 724
 
6.8%
94 670
 
6.3%
98 619
 
5.8%
93 590
 
5.5%
90 584
 
5.5%
92 582
 
5.5%
99 525
 
4.9%
Other values (36) 3840
36.0%
ValueCountFrequency (%)
-26 1
 
< 0.1%
-15 1
 
< 0.1%
-13 1
 
< 0.1%
-5 2
< 0.1%
-3 1
 
< 0.1%
56 1
 
< 0.1%
60 3
< 0.1%
62 1
 
< 0.1%
63 1
 
< 0.1%
64 3
< 0.1%
ValueCountFrequency (%)
100 1001
9.4%
99 525
4.9%
98 619
5.8%
97 744
7.0%
96 724
6.8%
95 797
7.5%
94 670
6.3%
93 590
5.5%
92 582
5.5%
91 513
4.8%

Street Number
Real number (ℝ)

High correlation 

Distinct3004
Distinct (%)28.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5576.902
Minimum0
Maximum39779
Zeros7
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size83.5 KiB
2025-04-14T23:23:43.966177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile445
Q12323.75
median4321
Q38301
95-th percentile13440
Maximum39779
Range39779
Interquartile range (IQR)5977.25

Descriptive statistics

Standard deviation4351.7927
Coefficient of variation (CV)0.78032439
Kurtosis3.8372489
Mean5576.902
Median Absolute Deviation (MAD)2674.5
Skewness1.3324765
Sum59539006
Variance18938099
MonotonicityNot monotonic
2025-04-14T23:23:44.115587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8008 80
 
0.7%
2500 68
 
0.6%
8687 51
 
0.5%
13350 46
 
0.4%
921 42
 
0.4%
400 37
 
0.3%
1515 37
 
0.3%
3000 36
 
0.3%
650 34
 
0.3%
9780 34
 
0.3%
Other values (2994) 10211
95.6%
ValueCountFrequency (%)
0 7
0.1%
100 7
0.1%
102 7
0.1%
103 1
 
< 0.1%
104 2
 
< 0.1%
105 1
 
< 0.1%
106 5
< 0.1%
108 2
 
< 0.1%
110 5
< 0.1%
111 8
0.1%
ValueCountFrequency (%)
39779 4
< 0.1%
39739 2
 
< 0.1%
39718 2
 
< 0.1%
39640 3
< 0.1%
19304 2
 
< 0.1%
19177 2
 
< 0.1%
19160 2
 
< 0.1%
19129 5
< 0.1%
19111 2
 
< 0.1%
19090 1
 
< 0.1%
Distinct750
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size677.2 KiB
2025-04-14T23:23:44.485367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length25
Median length21
Mean length7.9466092
Min length2

Characters and Unicode

Total characters84838
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique143 ?
Unique (%)1.3%

Sample

1st rowGRAND
2nd rowNORTHWEST
3rd rowPRESTON
4th rowKIEST
5th rowCOMMERCE
ValueCountFrequency (%)
preston 345
 
2.6%
northwest 323
 
2.5%
forest 279
 
2.1%
buckner 261
 
2.0%
central 241
 
1.8%
greenville 225
 
1.7%
hill 215
 
1.6%
walnut 193
 
1.5%
mockingbird 163
 
1.2%
illinois 161
 
1.2%
Other values (779) 10757
81.7%
2025-04-14T23:23:44.961005image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 8454
 
10.0%
R 7246
 
8.5%
L 7061
 
8.3%
N 6715
 
7.9%
A 6635
 
7.8%
O 5843
 
6.9%
T 5074
 
6.0%
S 4867
 
5.7%
I 4633
 
5.5%
M 3142
 
3.7%
Other values (30) 25168
29.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 84838
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 8454
 
10.0%
R 7246
 
8.5%
L 7061
 
8.3%
N 6715
 
7.9%
A 6635
 
7.8%
O 5843
 
6.9%
T 5074
 
6.0%
S 4867
 
5.7%
I 4633
 
5.5%
M 3142
 
3.7%
Other values (30) 25168
29.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 84838
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 8454
 
10.0%
R 7246
 
8.5%
L 7061
 
8.3%
N 6715
 
7.9%
A 6635
 
7.8%
O 5843
 
6.9%
T 5074
 
6.0%
S 4867
 
5.7%
I 4633
 
5.5%
M 3142
 
3.7%
Other values (30) 25168
29.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 84838
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 8454
 
10.0%
R 7246
 
8.5%
L 7061
 
8.3%
N 6715
 
7.9%
A 6635
 
7.8%
O 5843
 
6.9%
T 5074
 
6.0%
S 4867
 
5.7%
I 4633
 
5.5%
M 3142
 
3.7%
Other values (30) 25168
29.7%

Street Direction
Categorical

High correlation  Missing 

Distinct4
Distinct (%)0.1%
Missing6947
Missing (%)65.1%
Memory size645.5 KiB
W
1246 
S
1023 
N
973 
E
487 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3729
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowE
2nd rowW
3rd rowW
4th rowS
5th rowS

Common Values

ValueCountFrequency (%)
W 1246
 
11.7%
S 1023
 
9.6%
N 973
 
9.1%
E 487
 
4.6%
(Missing) 6947
65.1%

Length

2025-04-14T23:23:45.090763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:23:45.163211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
w 1246
33.4%
s 1023
27.4%
n 973
26.1%
e 487
 
13.1%

Most occurring characters

ValueCountFrequency (%)
W 1246
33.4%
S 1023
27.4%
N 973
26.1%
E 487
 
13.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3729
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
W 1246
33.4%
S 1023
27.4%
N 973
26.1%
E 487
 
13.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3729
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
W 1246
33.4%
S 1023
27.4%
N 973
26.1%
E 487
 
13.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3729
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
W 1246
33.4%
S 1023
27.4%
N 973
26.1%
E 487
 
13.1%

Street Type
Categorical

High correlation  Missing 

Distinct19
Distinct (%)0.2%
Missing220
Missing (%)2.1%
Memory size622.3 KiB
RD
2839 
AVE
1652 
ST
1540 
LN
1152 
BLVD
1071 
Other values (14)
2202 

Length

Max length4
Median length2
Mean length2.5892311
Min length2

Characters and Unicode

Total characters27073
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAVE
2nd rowHWY
3rd rowRD
4th rowBLVD
5th rowST

Common Values

ValueCountFrequency (%)
RD 2839
26.6%
AVE 1652
15.5%
ST 1540
14.4%
LN 1152
10.8%
BLVD 1071
 
10.0%
DR 720
 
6.7%
FRWY 394
 
3.7%
HWY 323
 
3.0%
EXPW 255
 
2.4%
PKWY 247
 
2.3%
Other values (9) 263
 
2.5%
(Missing) 220
 
2.1%

Length

2025-04-14T23:23:45.267762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
rd 2839
27.2%
ave 1652
15.8%
st 1540
14.7%
ln 1152
11.0%
blvd 1071
 
10.2%
dr 720
 
6.9%
frwy 394
 
3.8%
hwy 323
 
3.1%
expw 255
 
2.4%
pkwy 247
 
2.4%
Other values (9) 263
 
2.5%

Most occurring characters

ValueCountFrequency (%)
D 4630
17.1%
R 4015
14.8%
V 2723
10.1%
L 2260
8.3%
E 1957
7.2%
A 1764
 
6.5%
T 1640
 
6.1%
S 1546
 
5.7%
W 1362
 
5.0%
N 1152
 
4.3%
Other values (11) 4024
14.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27073
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
D 4630
17.1%
R 4015
14.8%
V 2723
10.1%
L 2260
8.3%
E 1957
7.2%
A 1764
 
6.5%
T 1640
 
6.1%
S 1546
 
5.7%
W 1362
 
5.0%
N 1152
 
4.3%
Other values (11) 4024
14.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27073
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
D 4630
17.1%
R 4015
14.8%
V 2723
10.1%
L 2260
8.3%
E 1957
7.2%
A 1764
 
6.5%
T 1640
 
6.1%
S 1546
 
5.7%
W 1362
 
5.0%
N 1152
 
4.3%
Other values (11) 4024
14.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27073
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
D 4630
17.1%
R 4015
14.8%
V 2723
10.1%
L 2260
8.3%
E 1957
7.2%
A 1764
 
6.5%
T 1640
 
6.1%
S 1546
 
5.7%
W 1362
 
5.0%
N 1152
 
4.3%
Other values (11) 4024
14.9%

Street Unit
Text

Missing 

Distinct726
Distinct (%)19.4%
Missing6941
Missing (%)65.0%
Memory size438.9 KiB
2025-04-14T23:23:45.650542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.8190094
Min length1

Characters and Unicode

Total characters14264
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique293 ?
Unique (%)7.8%

Sample

1st row#300
2nd row#1101
3rd row#351
4th rowC2216
5th row#108
ValueCountFrequency (%)
100 426
 
11.4%
110 157
 
4.2%
a 151
 
4.0%
101 127
 
3.4%
b 100
 
2.7%
120 82
 
2.2%
300 78
 
2.1%
102 78
 
2.1%
200 68
 
1.8%
130 65
 
1.7%
Other values (641) 2419
64.5%
2025-04-14T23:23:46.155891image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
# 3295
23.1%
0 3113
21.8%
1 3020
21.2%
2 1087
 
7.6%
3 673
 
4.7%
5 552
 
3.9%
4 458
 
3.2%
6 385
 
2.7%
8 276
 
1.9%
7 265
 
1.9%
Other values (26) 1140
 
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14264
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
# 3295
23.1%
0 3113
21.8%
1 3020
21.2%
2 1087
 
7.6%
3 673
 
4.7%
5 552
 
3.9%
4 458
 
3.2%
6 385
 
2.7%
8 276
 
1.9%
7 265
 
1.9%
Other values (26) 1140
 
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14264
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
# 3295
23.1%
0 3113
21.8%
1 3020
21.2%
2 1087
 
7.6%
3 673
 
4.7%
5 552
 
3.9%
4 458
 
3.2%
6 385
 
2.7%
8 276
 
1.9%
7 265
 
1.9%
Other values (26) 1140
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14264
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
# 3295
23.1%
0 3113
21.8%
1 3020
21.2%
2 1087
 
7.6%
3 673
 
4.7%
5 552
 
3.9%
4 458
 
3.2%
6 385
 
2.7%
8 276
 
1.9%
7 265
 
1.9%
Other values (26) 1140
 
8.0%
Distinct5773
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Memory size792.9 KiB
2025-04-14T23:23:46.528814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length37
Median length32
Mean length19.041963
Min length10

Characters and Unicode

Total characters203292
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2719 ?
Unique (%)25.5%

Sample

1st row3100 GRAND AVE
2nd row10677 E NORTHWEST HWY #300
3rd row10720 PRESTON RD #1101
4th row6777 W KIEST BLVD
5th row1000 COMMERCE ST
ValueCountFrequency (%)
rd 2841
 
6.7%
ave 1653
 
3.9%
st 1594
 
3.8%
w 1257
 
3.0%
ln 1157
 
2.7%
blvd 1077
 
2.6%
s 1028
 
2.4%
n 973
 
2.3%
dr 720
 
1.7%
e 512
 
1.2%
Other values (4281) 29328
69.6%
2025-04-14T23:23:47.024139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31464
 
15.5%
R 11310
 
5.6%
E 11193
 
5.5%
1 10676
 
5.3%
0 10326
 
5.1%
L 9415
 
4.6%
N 8852
 
4.4%
A 8675
 
4.3%
S 7688
 
3.8%
D 6996
 
3.4%
Other values (34) 86697
42.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 203292
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
31464
 
15.5%
R 11310
 
5.6%
E 11193
 
5.5%
1 10676
 
5.3%
0 10326
 
5.1%
L 9415
 
4.6%
N 8852
 
4.4%
A 8675
 
4.3%
S 7688
 
3.8%
D 6996
 
3.4%
Other values (34) 86697
42.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 203292
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
31464
 
15.5%
R 11310
 
5.6%
E 11193
 
5.5%
1 10676
 
5.3%
0 10326
 
5.1%
L 9415
 
4.6%
N 8852
 
4.4%
A 8675
 
4.3%
S 7688
 
3.8%
D 6996
 
3.4%
Other values (34) 86697
42.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 203292
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
31464
 
15.5%
R 11310
 
5.6%
E 11193
 
5.5%
1 10676
 
5.3%
0 10326
 
5.1%
L 9415
 
4.6%
N 8852
 
4.4%
A 8675
 
4.3%
S 7688
 
3.8%
D 6996
 
3.4%
Other values (34) 86697
42.6%
Distinct134
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size646.9 KiB
2025-04-14T23:23:47.258543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.0342825
Min length5

Characters and Unicode

Total characters53746
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)0.3%

Sample

1st row75215
2nd row75238
3rd row75230
4th row75211
5th row75202
ValueCountFrequency (%)
75201 500
 
4.7%
75211 487
 
4.6%
75220 486
 
4.6%
75208 474
 
4.4%
75217 453
 
4.2%
75243 423
 
4.0%
75231 404
 
3.8%
75206 388
 
3.6%
75228 343
 
3.2%
75229 320
 
3.0%
Other values (124) 6398
59.9%
2025-04-14T23:23:47.570740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13556
25.2%
7 12075
22.5%
5 11831
22.0%
1 3947
 
7.3%
0 3643
 
6.8%
3 2693
 
5.0%
4 2443
 
4.5%
8 1658
 
3.1%
6 1025
 
1.9%
9 809
 
1.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 53746
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 13556
25.2%
7 12075
22.5%
5 11831
22.0%
1 3947
 
7.3%
0 3643
 
6.8%
3 2693
 
5.0%
4 2443
 
4.5%
8 1658
 
3.1%
6 1025
 
1.9%
9 809
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 53746
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 13556
25.2%
7 12075
22.5%
5 11831
22.0%
1 3947
 
7.3%
0 3643
 
6.8%
3 2693
 
5.0%
4 2443
 
4.5%
8 1658
 
3.1%
6 1025
 
1.9%
9 809
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 53746
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 13556
25.2%
7 12075
22.5%
5 11831
22.0%
1 3947
 
7.3%
0 3643
 
6.8%
3 2693
 
5.0%
4 2443
 
4.5%
8 1658
 
3.1%
6 1025
 
1.9%
9 809
 
1.5%
Distinct348
Distinct (%)3.6%
Missing1002
Missing (%)9.4%
Memory size1.0 MiB
2025-04-14T23:23:47.827140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length91
Mean length42.98129
Min length12

Characters and Unicode

Total characters415801
Distinct characters80
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)0.9%

Sample

1st row*10 Clean Sight and Touch
2nd row*24 Food Labeling- with common name of the food
3rd row*45 Drying Mops-air dry
4th row*39 Store equipment & utensils in a clean, dry place
5th row*31 Handwashing lavatory - used for other purpose
ValueCountFrequency (%)
food 2541
 
3.8%
2102
 
3.1%
and 1610
 
2.4%
or 1320
 
2.0%
10 1296
 
1.9%
in 1048
 
1.6%
not 1001
 
1.5%
clean 973
 
1.4%
touch 896
 
1.3%
sight 896
 
1.3%
Other values (842) 53540
79.6%
2025-04-14T23:23:48.232550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58619
 
14.1%
o 31355
 
7.5%
e 31217
 
7.5%
n 24792
 
6.0%
t 23967
 
5.8%
i 23417
 
5.6%
a 21826
 
5.2%
r 18311
 
4.4%
s 17571
 
4.2%
d 16374
 
3.9%
Other values (70) 148352
35.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 415801
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
58619
 
14.1%
o 31355
 
7.5%
e 31217
 
7.5%
n 24792
 
6.0%
t 23967
 
5.8%
i 23417
 
5.6%
a 21826
 
5.2%
r 18311
 
4.4%
s 17571
 
4.2%
d 16374
 
3.9%
Other values (70) 148352
35.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 415801
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
58619
 
14.1%
o 31355
 
7.5%
e 31217
 
7.5%
n 24792
 
6.0%
t 23967
 
5.8%
i 23417
 
5.6%
a 21826
 
5.2%
r 18311
 
4.4%
s 17571
 
4.2%
d 16374
 
3.9%
Other values (70) 148352
35.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 415801
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
58619
 
14.1%
o 31355
 
7.5%
e 31217
 
7.5%
n 24792
 
6.0%
t 23967
 
5.8%
i 23417
 
5.6%
a 21826
 
5.2%
r 18311
 
4.4%
s 17571
 
4.2%
d 16374
 
3.9%
Other values (70) 148352
35.7%

Violation Points - 1
Categorical

High correlation  Missing 

Distinct3
Distinct (%)< 0.1%
Missing1002
Missing (%)9.4%
Memory size629.6 KiB
3.0
4305 
1.0
2869 
2.0
2500 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters29022
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.0
2nd row2.0
3rd row1.0
4th row1.0
5th row2.0

Common Values

ValueCountFrequency (%)
3.0 4305
40.3%
1.0 2869
26.9%
2.0 2500
23.4%
(Missing) 1002
 
9.4%

Length

2025-04-14T23:23:48.341335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:23:48.406444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
3.0 4305
44.5%
1.0 2869
29.7%
2.0 2500
25.8%

Most occurring characters

ValueCountFrequency (%)
. 9674
33.3%
0 9674
33.3%
3 4305
14.8%
1 2869
 
9.9%
2 2500
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 29022
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 9674
33.3%
0 9674
33.3%
3 4305
14.8%
1 2869
 
9.9%
2 2500
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 29022
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 9674
33.3%
0 9674
33.3%
3 4305
14.8%
1 2869
 
9.9%
2 2500
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 29022
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 9674
33.3%
0 9674
33.3%
3 4305
14.8%
1 2869
 
9.9%
2 2500
 
8.6%

Violation Detail - 1
Text

Missing 

Distinct352
Distinct (%)3.7%
Missing1085
Missing (%)10.2%
Memory size4.6 MiB
2025-04-14T23:23:48.661438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length910
Median length731
Mean length366.99677
Min length125

Characters and Unicode

Total characters3519866
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)0.9%

Sample

1st row228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. Equipment, food-contact surfaces, non-food contact surfaces and utensils. (1) Equipment food-contact surfaces and utensils shall be clean to sight and touch.
2nd row228.79 Food. Labeling. (a) Food labels. (2) Label information shall include: (A) the common name of the food, or absent a common name, an adequately descriptive identity statement;
3rd row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (f) Drying mops. After use, mops shall be placed in a position that allows them to air-dry without soiling walls, equipment, or supplies.
4th row228.124 Equipment, Utensils, and Linens. Storage. (a) Equipment, utensils, linens, and single-service and single-use articles. (1) Except as specified in paragraph (4) of this subsection, cleaned equipment and utensils, laundered linens, and single-service and single-use articles shall be stored: (A) in a clean, dry location;
5th row228.149 Water, Plumbing, and Waste. Plumbing, operation and maintenance. (a) Using a handwashing facility. (2) A handwashing facility may not be used for purposes other than handwashing.
ValueCountFrequency (%)
and 28363
 
5.8%
food 19379
 
4.0%
of 16781
 
3.4%
the 14503
 
3.0%
a 12542
 
2.6%
shall 11237
 
2.3%
in 11140
 
2.3%
equipment 10317
 
2.1%
be 9618
 
2.0%
or 8802
 
1.8%
Other values (1864) 344932
70.7%
2025-04-14T23:23:49.088959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
719124
20.4%
e 296453
 
8.4%
a 204913
 
5.8%
n 203343
 
5.8%
i 199753
 
5.7%
t 199647
 
5.7%
o 191463
 
5.4%
s 185151
 
5.3%
r 139351
 
4.0%
d 120181
 
3.4%
Other values (62) 1060487
30.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3519866
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
719124
20.4%
e 296453
 
8.4%
a 204913
 
5.8%
n 203343
 
5.8%
i 199753
 
5.7%
t 199647
 
5.7%
o 191463
 
5.4%
s 185151
 
5.3%
r 139351
 
4.0%
d 120181
 
3.4%
Other values (62) 1060487
30.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3519866
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
719124
20.4%
e 296453
 
8.4%
a 204913
 
5.8%
n 203343
 
5.8%
i 199753
 
5.7%
t 199647
 
5.7%
o 191463
 
5.4%
s 185151
 
5.3%
r 139351
 
4.0%
d 120181
 
3.4%
Other values (62) 1060487
30.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3519866
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
719124
20.4%
e 296453
 
8.4%
a 204913
 
5.8%
n 203343
 
5.8%
i 199753
 
5.7%
t 199647
 
5.7%
o 191463
 
5.4%
s 185151
 
5.3%
r 139351
 
4.0%
d 120181
 
3.4%
Other values (62) 1060487
30.1%

Violation Memo - 1
Text

Missing 

Distinct7549
Distinct (%)87.2%
Missing2023
Missing (%)18.9%
Memory size982.5 KiB
2025-04-14T23:23:49.446264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1851
Median length217
Mean length51.778227
Min length3

Characters and Unicode

Total characters448037
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7098 ?
Unique (%)82.0%

Sample

1st rowCLEAN INSIDE OF ICE MACHINE
2nd rowlabel squeeze bottles
3rd rowhang mops when not in use
4th rowice scoop
5th rowdo not use hand sink as dump sink
ValueCountFrequency (%)
in 2031
 
2.7%
observed 1616
 
2.1%
food 1457
 
1.9%
at 1433
 
1.9%
clean 1398
 
1.8%
on 1274
 
1.7%
of 1224
 
1.6%
and 1175
 
1.5%
985
 
1.3%
to 952
 
1.3%
Other values (4404) 62604
82.2%
2025-04-14T23:23:49.960228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70166
 
15.7%
e 34513
 
7.7%
o 23152
 
5.2%
a 21200
 
4.7%
n 19204
 
4.3%
i 18879
 
4.2%
r 18667
 
4.2%
t 18493
 
4.1%
s 17394
 
3.9%
d 13287
 
3.0%
Other values (77) 193082
43.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 448037
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
70166
 
15.7%
e 34513
 
7.7%
o 23152
 
5.2%
a 21200
 
4.7%
n 19204
 
4.3%
i 18879
 
4.2%
r 18667
 
4.2%
t 18493
 
4.1%
s 17394
 
3.9%
d 13287
 
3.0%
Other values (77) 193082
43.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 448037
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
70166
 
15.7%
e 34513
 
7.7%
o 23152
 
5.2%
a 21200
 
4.7%
n 19204
 
4.3%
i 18879
 
4.2%
r 18667
 
4.2%
t 18493
 
4.1%
s 17394
 
3.9%
d 13287
 
3.0%
Other values (77) 193082
43.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 448037
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
70166
 
15.7%
e 34513
 
7.7%
o 23152
 
5.2%
a 21200
 
4.7%
n 19204
 
4.3%
i 18879
 
4.2%
r 18667
 
4.2%
t 18493
 
4.1%
s 17394
 
3.9%
d 13287
 
3.0%
Other values (77) 193082
43.1%
Distinct360
Distinct (%)4.2%
Missing2108
Missing (%)19.7%
Memory size917.2 KiB
2025-04-14T23:23:50.300336image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length84
Mean length43.34092
Min length12

Characters and Unicode

Total characters371345
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)1.2%

Sample

1st row*42 Dirty nonfood contact surfaces
2nd row*29 Sanitizing solutions, testing devices
3rd row*42 Dirty nonfood contact surfaces
4th row*22 Accredited food handler certificate - 60 days
5th row*47 Other Violations
ValueCountFrequency (%)
food 2266
 
3.8%
1954
 
3.3%
in 1038
 
1.7%
and 1024
 
1.7%
42 821
 
1.4%
dirty 774
 
1.3%
not 762
 
1.3%
10 735
 
1.2%
good 716
 
1.2%
or 661
 
1.1%
Other values (865) 48600
81.9%
2025-04-14T23:23:50.768187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51683
13.9%
e 28946
 
7.8%
o 26852
 
7.2%
i 22863
 
6.2%
n 22801
 
6.1%
t 22110
 
6.0%
a 19558
 
5.3%
s 17873
 
4.8%
r 16918
 
4.6%
d 13538
 
3.6%
Other values (69) 128203
34.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 371345
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
51683
13.9%
e 28946
 
7.8%
o 26852
 
7.2%
i 22863
 
6.2%
n 22801
 
6.1%
t 22110
 
6.0%
a 19558
 
5.3%
s 17873
 
4.8%
r 16918
 
4.6%
d 13538
 
3.6%
Other values (69) 128203
34.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 371345
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
51683
13.9%
e 28946
 
7.8%
o 26852
 
7.2%
i 22863
 
6.2%
n 22801
 
6.1%
t 22110
 
6.0%
a 19558
 
5.3%
s 17873
 
4.8%
r 16918
 
4.6%
d 13538
 
3.6%
Other values (69) 128203
34.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 371345
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
51683
13.9%
e 28946
 
7.8%
o 26852
 
7.2%
i 22863
 
6.2%
n 22801
 
6.1%
t 22110
 
6.0%
a 19558
 
5.3%
s 17873
 
4.8%
r 16918
 
4.6%
d 13538
 
3.6%
Other values (69) 128203
34.5%

Violation Points - 2
Categorical

High correlation  Missing 

Distinct3
Distinct (%)< 0.1%
Missing2108
Missing (%)19.7%
Memory size633.9 KiB
1.0
3537 
2.0
2717 
3.0
2314 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters25704
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row2.0
3rd row1.0
4th row2.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 3537
33.1%
2.0 2717
25.4%
3.0 2314
21.7%
(Missing) 2108
19.7%

Length

2025-04-14T23:23:50.874712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:23:50.938997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3537
41.3%
2.0 2717
31.7%
3.0 2314
27.0%

Most occurring characters

ValueCountFrequency (%)
. 8568
33.3%
0 8568
33.3%
1 3537
13.8%
2 2717
 
10.6%
3 2314
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25704
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 8568
33.3%
0 8568
33.3%
1 3537
13.8%
2 2717
 
10.6%
3 2314
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25704
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 8568
33.3%
0 8568
33.3%
1 3537
13.8%
2 2717
 
10.6%
3 2314
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25704
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 8568
33.3%
0 8568
33.3%
1 3537
13.8%
2 2717
 
10.6%
3 2314
 
9.0%

Violation Detail - 2
Text

Missing 

Distinct365
Distinct (%)4.3%
Missing2205
Missing (%)20.7%
Memory size3.9 MiB
2025-04-14T23:23:51.243936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length910
Median length703
Mean length353.9274
Min length125

Characters and Unicode

Total characters2998119
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)1.2%

Sample

1st row228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.
2nd row228.108 Equipment, Utensils, and Linens. Utensils, temperature measuring devices, and testing devices. (e) Sanitizing solutions, testing device. A test kit or other device that accurately measures the concentration in mg/L of sanitizing solutions shall be provided.
3rd row228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.
4th rowõ228.33. Certified Food Protection Manager and Food Handler Requirements (d) Except in a temporary food establishment and the certified food manager, all food employees shall successfully complete an accredited food handler training course, within 60 days of employment.
5th row228.42 Management and Personnel. Food Contamination Prevention (a) Eating, drinking, or using tobacco. (1) except as specified in paragraph (2) of this subsection, an employee shall eat, drink, or use any form of tobacco only in designated areas where the contamination of exposed food; clean equipment, utensils, and linens; unwrapped single-service and single-use articles; or other items needing protection cannot result.
ValueCountFrequency (%)
and 22965
 
5.6%
food 16918
 
4.1%
of 14441
 
3.5%
the 13899
 
3.4%
a 11698
 
2.8%
shall 9818
 
2.4%
equipment 9169
 
2.2%
in 9115
 
2.2%
be 8418
 
2.0%
or 6561
 
1.6%
Other values (1913) 290239
70.2%
2025-04-14T23:23:51.730859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
604532
20.2%
e 255712
 
8.5%
a 175362
 
5.8%
n 175041
 
5.8%
i 172674
 
5.8%
t 170838
 
5.7%
s 160868
 
5.4%
o 160409
 
5.4%
r 119052
 
4.0%
d 101660
 
3.4%
Other values (65) 901971
30.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2998119
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
604532
20.2%
e 255712
 
8.5%
a 175362
 
5.8%
n 175041
 
5.8%
i 172674
 
5.8%
t 170838
 
5.7%
s 160868
 
5.4%
o 160409
 
5.4%
r 119052
 
4.0%
d 101660
 
3.4%
Other values (65) 901971
30.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2998119
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
604532
20.2%
e 255712
 
8.5%
a 175362
 
5.8%
n 175041
 
5.8%
i 172674
 
5.8%
t 170838
 
5.7%
s 160868
 
5.4%
o 160409
 
5.4%
r 119052
 
4.0%
d 101660
 
3.4%
Other values (65) 901971
30.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2998119
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
604532
20.2%
e 255712
 
8.5%
a 175362
 
5.8%
n 175041
 
5.8%
i 172674
 
5.8%
t 170838
 
5.7%
s 160868
 
5.4%
o 160409
 
5.4%
r 119052
 
4.0%
d 101660
 
3.4%
Other values (65) 901971
30.1%

Violation Memo - 2
Text

Missing 

Distinct6543
Distinct (%)87.4%
Missing3187
Missing (%)29.9%
Memory size867.0 KiB
2025-04-14T23:23:52.091506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1315
Median length175
Mean length47.731072
Min length2

Characters and Unicode

Total characters357458
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6133 ?
Unique (%)81.9%

Sample

1st rowclean bottom of RIF
2nd rowprovide chemical test strips to check the sanitizer
3rd rowcan't have newspaper/cardboard on shelves
4th rowCURRENT INSPECTION REPORT NOT POSTED OR SIGNAGE
5th rowObserved employee beverage on clean table in dish pit area
ValueCountFrequency (%)
in 1828
 
3.0%
food 1366
 
2.3%
clean 1260
 
2.1%
observed 1131
 
1.9%
on 1104
 
1.8%
of 1042
 
1.7%
and 930
 
1.5%
at 837
 
1.4%
to 779
 
1.3%
provide 745
 
1.2%
Other values (3599) 49334
81.7%
2025-04-14T23:23:52.730182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
53933
 
15.1%
e 28098
 
7.9%
o 19485
 
5.5%
a 17175
 
4.8%
n 16495
 
4.6%
r 15779
 
4.4%
i 15596
 
4.4%
t 15260
 
4.3%
s 14276
 
4.0%
d 10766
 
3.0%
Other values (77) 150595
42.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 357458
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
53933
 
15.1%
e 28098
 
7.9%
o 19485
 
5.5%
a 17175
 
4.8%
n 16495
 
4.6%
r 15779
 
4.4%
i 15596
 
4.4%
t 15260
 
4.3%
s 14276
 
4.0%
d 10766
 
3.0%
Other values (77) 150595
42.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 357458
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
53933
 
15.1%
e 28098
 
7.9%
o 19485
 
5.5%
a 17175
 
4.8%
n 16495
 
4.6%
r 15779
 
4.4%
i 15596
 
4.4%
t 15260
 
4.3%
s 14276
 
4.0%
d 10766
 
3.0%
Other values (77) 150595
42.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 357458
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
53933
 
15.1%
e 28098
 
7.9%
o 19485
 
5.5%
a 17175
 
4.8%
n 16495
 
4.6%
r 15779
 
4.4%
i 15596
 
4.4%
t 15260
 
4.3%
s 14276
 
4.0%
d 10766
 
3.0%
Other values (77) 150595
42.1%
Distinct343
Distinct (%)4.7%
Missing3384
Missing (%)31.7%
Memory size826.3 KiB
2025-04-14T23:23:53.025349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length84
Mean length43.501783
Min length12

Characters and Unicode

Total characters317215
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)1.4%

Sample

1st row*45 Mats / Duckboards nonabsorbent
2nd row*20 Grease Trap Tickets
3rd row*30 Does Establishment have a current valid permit posted?
4th row*45 Premises shall be maintained in good repair
5th row*34 Outer openings:closing holes, gaps
ValueCountFrequency (%)
food 1908
 
3.8%
1634
 
3.3%
in 848
 
1.7%
42 744
 
1.5%
dirty 710
 
1.4%
and 666
 
1.3%
of 634
 
1.3%
or 623
 
1.2%
good 589
 
1.2%
equipment 587
 
1.2%
Other values (847) 41224
82.2%
2025-04-14T23:23:53.964789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43595
 
13.7%
e 25052
 
7.9%
o 22987
 
7.2%
i 20084
 
6.3%
n 19382
 
6.1%
t 18864
 
5.9%
a 16037
 
5.1%
s 16032
 
5.1%
r 14490
 
4.6%
d 11400
 
3.6%
Other values (69) 109292
34.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 317215
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
43595
 
13.7%
e 25052
 
7.9%
o 22987
 
7.2%
i 20084
 
6.3%
n 19382
 
6.1%
t 18864
 
5.9%
a 16037
 
5.1%
s 16032
 
5.1%
r 14490
 
4.6%
d 11400
 
3.6%
Other values (69) 109292
34.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 317215
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
43595
 
13.7%
e 25052
 
7.9%
o 22987
 
7.2%
i 20084
 
6.3%
n 19382
 
6.1%
t 18864
 
5.9%
a 16037
 
5.1%
s 16032
 
5.1%
r 14490
 
4.6%
d 11400
 
3.6%
Other values (69) 109292
34.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 317215
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
43595
 
13.7%
e 25052
 
7.9%
o 22987
 
7.2%
i 20084
 
6.3%
n 19382
 
6.1%
t 18864
 
5.9%
a 16037
 
5.1%
s 16032
 
5.1%
r 14490
 
4.6%
d 11400
 
3.6%
Other values (69) 109292
34.5%

Violation Points - 3
Categorical

High correlation  Missing 

Distinct3
Distinct (%)< 0.1%
Missing3384
Missing (%)31.7%
Memory size638.9 KiB
1.0
3584 
2.0
2405 
3.0
1303 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters21876
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row3.0
3rd row2.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 3584
33.6%
2.0 2405
22.5%
3.0 1303
 
12.2%
(Missing) 3384
31.7%

Length

2025-04-14T23:23:54.134940image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:23:54.243103image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3584
49.1%
2.0 2405
33.0%
3.0 1303
 
17.9%

Most occurring characters

ValueCountFrequency (%)
. 7292
33.3%
0 7292
33.3%
1 3584
16.4%
2 2405
 
11.0%
3 1303
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21876
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 7292
33.3%
0 7292
33.3%
1 3584
16.4%
2 2405
 
11.0%
3 1303
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21876
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 7292
33.3%
0 7292
33.3%
1 3584
16.4%
2 2405
 
11.0%
3 1303
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21876
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 7292
33.3%
0 7292
33.3%
1 3584
16.4%
2 2405
 
11.0%
3 1303
 
6.0%

Violation Detail - 3
Text

Missing 

Distinct346
Distinct (%)4.8%
Missing3504
Missing (%)32.8%
Memory size3.3 MiB
2025-04-14T23:23:54.685881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length910
Median length691
Mean length348.34063
Min length125

Characters and Unicode

Total characters2498299
Distinct characters74
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)1.4%

Sample

1st rowSEC. 17-6.2. ADDITIONAL REQUIREMENTS. (c) Floors, walls, and ceilings. (2) Special requirements for floors. A food establishment shall: (C) use only mats and duckboards that are constructed of nonabsorbent, grease resistant material of a size, design, and construction that permits easy cleaning;
2nd rowCh.19-126.5(c)) A producer shall sign the manifest from the transporter when a load is picked up by the transporter and shall keep a copy of all trip tickets at the producer#s business office for three years. The director may inspect these records at any reasonable time.
3rd row228.247 COMPLIANCE Permit Requirement, Prerequisite for Operation A person may not operate a food establishment without a valid permit or license to operate issued by the regulatory authority.
4th row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (a) Repairing. The physical facilities shall be maintained in good repair.
5th row228.174 Physical Facilities. Functionality. (e) Outer openings, protected. (1) Except as specified in paragraphs (2) - (5) of this subsection, outer openings of a food establishment shall be protected against the entry of insects and rodents by: (A) filling or closing holes and other gaps along floors, walls and ceilings;
ValueCountFrequency (%)
and 18520
 
5.4%
food 14153
 
4.1%
of 12211
 
3.6%
the 11724
 
3.4%
a 9826
 
2.9%
shall 8178
 
2.4%
in 7507
 
2.2%
equipment 7295
 
2.1%
be 7111
 
2.1%
or 5538
 
1.6%
Other values (1880) 241405
70.3%
2025-04-14T23:23:55.305997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
506177
20.3%
e 213030
 
8.5%
i 145446
 
5.8%
a 145025
 
5.8%
n 144751
 
5.8%
t 141724
 
5.7%
s 134826
 
5.4%
o 133369
 
5.3%
r 99496
 
4.0%
d 84558
 
3.4%
Other values (64) 749897
30.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2498299
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
506177
20.3%
e 213030
 
8.5%
i 145446
 
5.8%
a 145025
 
5.8%
n 144751
 
5.8%
t 141724
 
5.7%
s 134826
 
5.4%
o 133369
 
5.3%
r 99496
 
4.0%
d 84558
 
3.4%
Other values (64) 749897
30.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2498299
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
506177
20.3%
e 213030
 
8.5%
i 145446
 
5.8%
a 145025
 
5.8%
n 144751
 
5.8%
t 141724
 
5.7%
s 134826
 
5.4%
o 133369
 
5.3%
r 99496
 
4.0%
d 84558
 
3.4%
Other values (64) 749897
30.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2498299
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
506177
20.3%
e 213030
 
8.5%
i 145446
 
5.8%
a 145025
 
5.8%
n 144751
 
5.8%
t 141724
 
5.7%
s 134826
 
5.4%
o 133369
 
5.3%
r 99496
 
4.0%
d 84558
 
3.4%
Other values (64) 749897
30.0%

Violation Memo - 3
Text

Missing 

Distinct5537
Distinct (%)87.5%
Missing4346
Missing (%)40.7%
Memory size787.5 KiB
2025-04-14T23:23:55.665990image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1615
Median length178
Mean length48.350869
Min length2

Characters and Unicode

Total characters306061
Distinct characters84
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5198 ?
Unique (%)82.1%

Sample

1st rowcan't have newspaper on floor
2nd rowCHANGE NAME OF ESTABLISHMENT
3rd rowFix small leak at 3CS
4th rowSeal all outer perimeters properly.
5th rowgaskets of RIC units observed with product debris accumulation
ValueCountFrequency (%)
in 1621
 
3.2%
food 1213
 
2.4%
clean 1027
 
2.0%
on 966
 
1.9%
observed 898
 
1.8%
of 795
 
1.6%
provide 752
 
1.5%
to 692
 
1.4%
and 690
 
1.3%
sink 616
 
1.2%
Other values (3143) 41866
81.9%
2025-04-14T23:23:56.180301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46632
 
15.2%
e 24090
 
7.9%
o 16783
 
5.5%
a 14448
 
4.7%
n 14165
 
4.6%
i 13409
 
4.4%
r 13341
 
4.4%
t 13207
 
4.3%
s 12595
 
4.1%
l 9218
 
3.0%
Other values (74) 128173
41.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 306061
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
46632
 
15.2%
e 24090
 
7.9%
o 16783
 
5.5%
a 14448
 
4.7%
n 14165
 
4.6%
i 13409
 
4.4%
r 13341
 
4.4%
t 13207
 
4.3%
s 12595
 
4.1%
l 9218
 
3.0%
Other values (74) 128173
41.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 306061
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
46632
 
15.2%
e 24090
 
7.9%
o 16783
 
5.5%
a 14448
 
4.7%
n 14165
 
4.6%
i 13409
 
4.4%
r 13341
 
4.4%
t 13207
 
4.3%
s 12595
 
4.1%
l 9218
 
3.0%
Other values (74) 128173
41.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 306061
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
46632
 
15.2%
e 24090
 
7.9%
o 16783
 
5.5%
a 14448
 
4.7%
n 14165
 
4.6%
i 13409
 
4.4%
r 13341
 
4.4%
t 13207
 
4.3%
s 12595
 
4.1%
l 9218
 
3.0%
Other values (74) 128173
41.9%
Distinct318
Distinct (%)5.3%
Missing4643
Missing (%)43.5%
Memory size747.5 KiB
2025-04-14T23:23:56.372349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length86
Mean length44.403116
Min length12

Characters and Unicode

Total characters267884
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)1.5%

Sample

1st row*21 RFSM - Not On Site
2nd row*28 Date marking > 24 hrs,on site,temp 41F
3rd row*43 Clean vent syst:Intake/exhaust air ducts
4th row*30 Food Establishment Permit
5th row*47 Health permit posted
ValueCountFrequency (%)
food 1657
 
3.9%
1290
 
3.1%
in 776
 
1.8%
42 634
 
1.5%
dirty 613
 
1.5%
or 592
 
1.4%
the 537
 
1.3%
of 530
 
1.3%
and 503
 
1.2%
good 502
 
1.2%
Other values (807) 34544
81.9%
2025-04-14T23:23:56.726446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36741
13.7%
e 21202
 
7.9%
o 19575
 
7.3%
i 16994
 
6.3%
n 16375
 
6.1%
t 15737
 
5.9%
s 13744
 
5.1%
a 13521
 
5.0%
r 12613
 
4.7%
d 9651
 
3.6%
Other values (68) 91731
34.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 267884
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
36741
13.7%
e 21202
 
7.9%
o 19575
 
7.3%
i 16994
 
6.3%
n 16375
 
6.1%
t 15737
 
5.9%
s 13744
 
5.1%
a 13521
 
5.0%
r 12613
 
4.7%
d 9651
 
3.6%
Other values (68) 91731
34.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 267884
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
36741
13.7%
e 21202
 
7.9%
o 19575
 
7.3%
i 16994
 
6.3%
n 16375
 
6.1%
t 15737
 
5.9%
s 13744
 
5.1%
a 13521
 
5.0%
r 12613
 
4.7%
d 9651
 
3.6%
Other values (68) 91731
34.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 267884
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
36741
13.7%
e 21202
 
7.9%
o 19575
 
7.3%
i 16994
 
6.3%
n 16375
 
6.1%
t 15737
 
5.9%
s 13744
 
5.1%
a 13521
 
5.0%
r 12613
 
4.7%
d 9651
 
3.6%
Other values (68) 91731
34.2%

Violation Points - 4
Categorical

High correlation  Missing 

Distinct3
Distinct (%)< 0.1%
Missing4643
Missing (%)43.5%
Memory size643.8 KiB
1.0
3397 
2.0
1830 
3.0
806 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters18099
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row2.0
3rd row1.0
4th row2.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 3397
31.8%
2.0 1830
 
17.1%
3.0 806
 
7.5%
(Missing) 4643
43.5%

Length

2025-04-14T23:23:56.828995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:23:56.893285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 3397
56.3%
2.0 1830
30.3%
3.0 806
 
13.4%

Most occurring characters

ValueCountFrequency (%)
. 6033
33.3%
0 6033
33.3%
1 3397
18.8%
2 1830
 
10.1%
3 806
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18099
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 6033
33.3%
0 6033
33.3%
1 3397
18.8%
2 1830
 
10.1%
3 806
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18099
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 6033
33.3%
0 6033
33.3%
1 3397
18.8%
2 1830
 
10.1%
3 806
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18099
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 6033
33.3%
0 6033
33.3%
1 3397
18.8%
2 1830
 
10.1%
3 806
 
4.5%

Violation Detail - 4
Text

Missing 

Distinct324
Distinct (%)5.5%
Missing4771
Missing (%)44.7%
Memory size2.7 MiB
2025-04-14T23:23:57.213179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length910
Median length694
Mean length345.1917
Min length125

Characters and Unicode

Total characters2038357
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)1.5%

Sample

1st rowSec. 17-2.2(c)(1)(D) (c) Registered food service managers. (1) Registered food service managers required. (D) A food establishment shall have one registered food service manager employed and present in the establishment during all hours of operation, except that a registered food service manager serving multiple food establishments as authorized by Section 17-2.2(c)(1)(C) must only be present in the building in which the food establishment is located during all hours of operation.
2nd row228.75 Food. Time and temperature control. (g) Ready-to-eat, TCS food, date marking. (2) Except as specified in paragraphs (5) - (7) of this subsection, refrigerated, ready-to-eat, time/temperature controlled for safety food prepared and packaged by a food processing plant shall be clearly marked, at the time the original container is opened in a food establishment and held at a temperature of 41 degrees Fahrenheit (5 degrees Celsius) or less if the food is held for more than 24 hours, to indicate the date or day by which the food shall be consumed on the premises, sold, or discarded, based on the temperature and time combinations specified in paragraph (1) of this subsection: (A) the day the original container is opened in the food establishment shall be counted as day 1; and
3rd row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (d) Cleaning ventilation systems, nuisance and discharge prohibition. (1) Intake and exhaust air ducts shall be cleaned and filters changed so they are not a source of contamination by dust, dirt, and other materials.
4th rowSEC. 17-10.2. ADDITIONAL REQUIREMENTS. (c) Permits. (1) Requisite. A person shall not operate a food establishment inside the city without a permit issued by the director. A separate permit is required for: (A) each establishment that is under a separate ownership;
5th rowSEC. 17-10.2. ADDITIONAL REQUIREMENTS. (c) Permits. (11) Display. A food establishment that operates from a fixed facility shall display its permit in a frame with a glass cover at a prominent place inside the facility where it can be easily seen by the public.
ValueCountFrequency (%)
and 14914
 
5.3%
food 11523
 
4.1%
of 10087
 
3.6%
the 9174
 
3.3%
a 7833
 
2.8%
shall 6562
 
2.3%
in 6148
 
2.2%
equipment 5904
 
2.1%
be 5773
 
2.1%
or 4609
 
1.7%
Other values (1822) 196745
70.4%
2025-04-14T23:23:57.744169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
414236
20.3%
e 174404
 
8.6%
i 119958
 
5.9%
n 118303
 
5.8%
a 117144
 
5.7%
t 114611
 
5.6%
s 111038
 
5.4%
o 108459
 
5.3%
r 81037
 
4.0%
d 68204
 
3.3%
Other values (62) 610963
30.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2038357
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
414236
20.3%
e 174404
 
8.6%
i 119958
 
5.9%
n 118303
 
5.8%
a 117144
 
5.7%
t 114611
 
5.6%
s 111038
 
5.4%
o 108459
 
5.3%
r 81037
 
4.0%
d 68204
 
3.3%
Other values (62) 610963
30.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2038357
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
414236
20.3%
e 174404
 
8.6%
i 119958
 
5.9%
n 118303
 
5.8%
a 117144
 
5.7%
t 114611
 
5.6%
s 111038
 
5.4%
o 108459
 
5.3%
r 81037
 
4.0%
d 68204
 
3.3%
Other values (62) 610963
30.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2038357
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
414236
20.3%
e 174404
 
8.6%
i 119958
 
5.9%
n 118303
 
5.8%
a 117144
 
5.7%
t 114611
 
5.6%
s 111038
 
5.4%
o 108459
 
5.3%
r 81037
 
4.0%
d 68204
 
3.3%
Other values (62) 610963
30.0%

Violation Memo - 4
Text

Missing 

Distinct4693
Distinct (%)89.3%
Missing5422
Missing (%)50.8%
Memory size706.2 KiB
2025-04-14T23:23:58.090657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length845
Median length170
Mean length47.570613
Min length2

Characters and Unicode

Total characters249936
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4422 ?
Unique (%)84.2%

Sample

1st rowprovide RFSM
2nd rowSHALL DATE MARK FOR A MAX OF 7 DAYS
3rd rowPost health permit in public view.
4th rowchange name of establishment on health permit
5th rowno sanitizer 0 ppm chlorine
ValueCountFrequency (%)
in 1411
 
3.4%
food 1074
 
2.6%
clean 807
 
1.9%
on 792
 
1.9%
observed 699
 
1.7%
provide 686
 
1.6%
of 612
 
1.5%
and 576
 
1.4%
to 564
 
1.3%
the 546
 
1.3%
Other values (2750) 34334
81.6%
2025-04-14T23:23:58.612723image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38176
 
15.3%
e 19347
 
7.7%
o 14246
 
5.7%
a 11727
 
4.7%
n 11722
 
4.7%
r 11208
 
4.5%
i 10936
 
4.4%
t 10818
 
4.3%
s 10266
 
4.1%
l 7614
 
3.0%
Other values (71) 103876
41.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 249936
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
38176
 
15.3%
e 19347
 
7.7%
o 14246
 
5.7%
a 11727
 
4.7%
n 11722
 
4.7%
r 11208
 
4.5%
i 10936
 
4.4%
t 10818
 
4.3%
s 10266
 
4.1%
l 7614
 
3.0%
Other values (71) 103876
41.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 249936
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
38176
 
15.3%
e 19347
 
7.7%
o 14246
 
5.7%
a 11727
 
4.7%
n 11722
 
4.7%
r 11208
 
4.5%
i 10936
 
4.4%
t 10818
 
4.3%
s 10266
 
4.1%
l 7614
 
3.0%
Other values (71) 103876
41.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 249936
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
38176
 
15.3%
e 19347
 
7.7%
o 14246
 
5.7%
a 11727
 
4.7%
n 11722
 
4.7%
r 11208
 
4.5%
i 10936
 
4.4%
t 10818
 
4.3%
s 10266
 
4.1%
l 7614
 
3.0%
Other values (71) 103876
41.6%
Distinct293
Distinct (%)6.0%
Missing5815
Missing (%)54.5%
Memory size670.8 KiB
2025-04-14T23:23:58.925797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length87
Mean length44.99136
Min length12

Characters and Unicode

Total characters218703
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)1.8%

Sample

1st row*29 Food thermometers provided and accessible
2nd row*32 Equipment & Utensils resistant pit,chip, crazing
3rd row*36 Containers of chemical sanitizing solutions stored off the floor and used in a manner that preve
4th row*46 Enclosed toilet room w/self closing doors
5th row*22 Accredited food handler certificate - 60 days
ValueCountFrequency (%)
food 1349
 
3.9%
992
 
2.9%
in 645
 
1.9%
or 524
 
1.5%
42 512
 
1.5%
dirty 492
 
1.4%
of 462
 
1.3%
equipment 456
 
1.3%
the 438
 
1.3%
good 411
 
1.2%
Other values (777) 27988
81.7%
2025-04-14T23:23:59.380342image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29909
13.7%
e 17248
 
7.9%
o 16101
 
7.4%
i 14183
 
6.5%
n 13598
 
6.2%
t 12645
 
5.8%
s 11350
 
5.2%
a 11104
 
5.1%
r 10143
 
4.6%
d 7813
 
3.6%
Other values (69) 74609
34.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 218703
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
29909
13.7%
e 17248
 
7.9%
o 16101
 
7.4%
i 14183
 
6.5%
n 13598
 
6.2%
t 12645
 
5.8%
s 11350
 
5.2%
a 11104
 
5.1%
r 10143
 
4.6%
d 7813
 
3.6%
Other values (69) 74609
34.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 218703
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
29909
13.7%
e 17248
 
7.9%
o 16101
 
7.4%
i 14183
 
6.5%
n 13598
 
6.2%
t 12645
 
5.8%
s 11350
 
5.2%
a 11104
 
5.1%
r 10143
 
4.6%
d 7813
 
3.6%
Other values (69) 74609
34.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 218703
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
29909
13.7%
e 17248
 
7.9%
o 16101
 
7.4%
i 14183
 
6.5%
n 13598
 
6.2%
t 12645
 
5.8%
s 11350
 
5.2%
a 11104
 
5.1%
r 10143
 
4.6%
d 7813
 
3.6%
Other values (69) 74609
34.1%

Violation Points - 5
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.1%
Missing5815
Missing (%)54.5%
Memory size648.4 KiB
1.0
2855 
2.0
1376 
3.0
630 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters14583
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2.0
2nd row2.0
3rd row1.0
4th row1.0
5th row2.0

Common Values

ValueCountFrequency (%)
1.0 2855
26.7%
2.0 1376
 
12.9%
3.0 630
 
5.9%
(Missing) 5815
54.5%

Length

2025-04-14T23:23:59.497185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:23:59.571745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 2855
58.7%
2.0 1376
28.3%
3.0 630
 
13.0%

Most occurring characters

ValueCountFrequency (%)
. 4861
33.3%
0 4861
33.3%
1 2855
19.6%
2 1376
 
9.4%
3 630
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14583
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 4861
33.3%
0 4861
33.3%
1 2855
19.6%
2 1376
 
9.4%
3 630
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14583
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 4861
33.3%
0 4861
33.3%
1 2855
19.6%
2 1376
 
9.4%
3 630
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14583
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 4861
33.3%
0 4861
33.3%
1 2855
19.6%
2 1376
 
9.4%
3 630
 
4.3%

Violation Detail - 5
Text

Missing 

Distinct298
Distinct (%)6.3%
Missing5917
Missing (%)55.4%
Memory size2.2 MiB
2025-04-14T23:24:00.239671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length888
Median length666
Mean length344.64404
Min length125

Characters and Unicode

Total characters1640161
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique84 ?
Unique (%)1.8%

Sample

1st row228.108 Equipment, Utensils, and Linens. Utensils, temperature measuring devices, and testing devices. (b) Food temperature measuring devices. Food temperature measuring devices shall be provided readily accessible for use in ensuring attainment and maintenance of food temperatures as specified under Subchapter C of this chapter (relating to Food).
2nd row228.101 Equipment, Utensils, and Linens. Multiuse materials. (a) Characteristics. Materials that are used in the construction of utensils and food-contact surfaces of equipment may not allow the migration of deleterious substances or impart colors, odors, or tastes to food and under normal use conditions shall be: (5) resistant to pitting, chipping, crazing, scratching, scoring, distortion, and decomposition.
3rd row228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (d) Wiping cloths, use limitation. (5) containers of chemical sanitizing solutions specified in paragraph (2)(A) of this subsection in which wet wiping cloths are held between uses shall be stored off the floor and used in a manner that prevents contamination of food, equipment, utensils, linens, single-service, or single-use articles. .
4th row228.174 Physical Facilities. Functionality. (d) A toilet room located on the premises shall be completely enclosed and provided with a tight-fitting and self-closing door except that this requirement does not apply to a toilet room that is located outside a food establishment and does not open directly into the food establishment such as a toilet room that is provided by the management of a shopping mall.
5th rowõ228.33. Certified Food Protection Manager and Food Handler Requirements (d) Except in a temporary food establishment and the certified food manager, all food employees shall successfully complete an accredited food handler training course, within 60 days of employment.
ValueCountFrequency (%)
and 12298
 
5.5%
food 8959
 
4.0%
of 8104
 
3.6%
the 7372
 
3.3%
a 6177
 
2.8%
shall 5298
 
2.4%
equipment 4928
 
2.2%
in 4916
 
2.2%
be 4772
 
2.1%
or 3918
 
1.7%
Other values (1750) 157683
70.3%
2025-04-14T23:24:00.901530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
335563
20.5%
e 138298
 
8.4%
i 96775
 
5.9%
n 95918
 
5.8%
a 94541
 
5.8%
t 92010
 
5.6%
s 89542
 
5.5%
o 87954
 
5.4%
r 64538
 
3.9%
d 54714
 
3.3%
Other values (61) 490308
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1640161
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
335563
20.5%
e 138298
 
8.4%
i 96775
 
5.9%
n 95918
 
5.8%
a 94541
 
5.8%
t 92010
 
5.6%
s 89542
 
5.5%
o 87954
 
5.4%
r 64538
 
3.9%
d 54714
 
3.3%
Other values (61) 490308
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1640161
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
335563
20.5%
e 138298
 
8.4%
i 96775
 
5.9%
n 95918
 
5.8%
a 94541
 
5.8%
t 92010
 
5.6%
s 89542
 
5.5%
o 87954
 
5.4%
r 64538
 
3.9%
d 54714
 
3.3%
Other values (61) 490308
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1640161
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
335563
20.5%
e 138298
 
8.4%
i 96775
 
5.9%
n 95918
 
5.8%
a 94541
 
5.8%
t 92010
 
5.6%
s 89542
 
5.5%
o 87954
 
5.4%
r 64538
 
3.9%
d 54714
 
3.3%
Other values (61) 490308
29.9%

Violation Memo - 5
Text

Missing 

Distinct3814
Distinct (%)89.5%
Missing6413
Missing (%)60.1%
Memory size632.4 KiB
2025-04-14T23:24:01.295404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1634
Median length142
Mean length46.736336
Min length2

Characters and Unicode

Total characters199237
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3600 ?
Unique (%)84.4%

Sample

1st rowprovide thermometers for RIC and RIF
2nd rowrestroom door shall be closed
3rd rowco worker has no food handler
4th rowNeed to provide last health inspection report available upon request.
5th rowprovide tarshcan for paper towels by hand sink
ValueCountFrequency (%)
in 1111
 
3.3%
food 822
 
2.5%
clean 696
 
2.1%
on 634
 
1.9%
observed 543
 
1.6%
provide 515
 
1.5%
of 499
 
1.5%
and 485
 
1.5%
not 440
 
1.3%
to 414
 
1.2%
Other values (2466) 27240
81.6%
2025-04-14T23:24:01.898073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30089
 
15.1%
e 15821
 
7.9%
o 11435
 
5.7%
n 9412
 
4.7%
a 9341
 
4.7%
r 9078
 
4.6%
i 8675
 
4.4%
t 8582
 
4.3%
s 8211
 
4.1%
l 6134
 
3.1%
Other values (73) 82459
41.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 199237
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
30089
 
15.1%
e 15821
 
7.9%
o 11435
 
5.7%
n 9412
 
4.7%
a 9341
 
4.7%
r 9078
 
4.6%
i 8675
 
4.4%
t 8582
 
4.3%
s 8211
 
4.1%
l 6134
 
3.1%
Other values (73) 82459
41.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 199237
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
30089
 
15.1%
e 15821
 
7.9%
o 11435
 
5.7%
n 9412
 
4.7%
a 9341
 
4.7%
r 9078
 
4.6%
i 8675
 
4.4%
t 8582
 
4.3%
s 8211
 
4.1%
l 6134
 
3.1%
Other values (73) 82459
41.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 199237
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
30089
 
15.1%
e 15821
 
7.9%
o 11435
 
5.7%
n 9412
 
4.7%
a 9341
 
4.7%
r 9078
 
4.6%
i 8675
 
4.4%
t 8582
 
4.3%
s 8211
 
4.1%
l 6134
 
3.1%
Other values (73) 82459
41.4%
Distinct277
Distinct (%)7.1%
Missing6794
Missing (%)63.6%
Memory size604.2 KiB
2025-04-14T23:24:02.269255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length83
Mean length45.364245
Min length12

Characters and Unicode

Total characters176104
Distinct characters80
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)2.3%

Sample

1st row*20 Grease Trap Tickets
2nd row*36 Cloths in-use for wiping between uses stored
3rd row*28 Date marking > 24 hrs,on site,temp 41F
4th row*29 Sanitizing solutions, testing devices
5th row*14 Gloves single use
ValueCountFrequency (%)
food 1128
 
4.1%
745
 
2.7%
in 534
 
2.0%
42 439
 
1.6%
dirty 414
 
1.5%
or 409
 
1.5%
equipment 378
 
1.4%
the 352
 
1.3%
good 338
 
1.2%
of 337
 
1.2%
Other values (754) 22269
81.4%
2025-04-14T23:24:02.821361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23909
13.6%
e 14055
 
8.0%
o 13131
 
7.5%
i 11394
 
6.5%
n 11089
 
6.3%
t 10338
 
5.9%
s 9241
 
5.2%
a 8721
 
5.0%
r 8503
 
4.8%
d 6313
 
3.6%
Other values (70) 59410
33.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 176104
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
23909
13.6%
e 14055
 
8.0%
o 13131
 
7.5%
i 11394
 
6.5%
n 11089
 
6.3%
t 10338
 
5.9%
s 9241
 
5.2%
a 8721
 
5.0%
r 8503
 
4.8%
d 6313
 
3.6%
Other values (70) 59410
33.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 176104
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
23909
13.6%
e 14055
 
8.0%
o 13131
 
7.5%
i 11394
 
6.5%
n 11089
 
6.3%
t 10338
 
5.9%
s 9241
 
5.2%
a 8721
 
5.0%
r 8503
 
4.8%
d 6313
 
3.6%
Other values (70) 59410
33.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 176104
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
23909
13.6%
e 14055
 
8.0%
o 13131
 
7.5%
i 11394
 
6.5%
n 11089
 
6.3%
t 10338
 
5.9%
s 9241
 
5.2%
a 8721
 
5.0%
r 8503
 
4.8%
d 6313
 
3.6%
Other values (70) 59410
33.7%

Violation Points - 6
Categorical

Missing 

Distinct3
Distinct (%)0.1%
Missing6794
Missing (%)63.6%
Memory size652.2 KiB
1.0
2453 
2.0
956 
3.0
473 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters11646
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.0
2nd row1.0
3rd row2.0
4th row2.0
5th row3.0

Common Values

ValueCountFrequency (%)
1.0 2453
 
23.0%
2.0 956
 
9.0%
3.0 473
 
4.4%
(Missing) 6794
63.6%

Length

2025-04-14T23:24:02.943114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:03.017749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 2453
63.2%
2.0 956
 
24.6%
3.0 473
 
12.2%

Most occurring characters

ValueCountFrequency (%)
. 3882
33.3%
0 3882
33.3%
1 2453
21.1%
2 956
 
8.2%
3 473
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11646
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 3882
33.3%
0 3882
33.3%
1 2453
21.1%
2 956
 
8.2%
3 473
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11646
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 3882
33.3%
0 3882
33.3%
1 2453
21.1%
2 956
 
8.2%
3 473
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11646
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 3882
33.3%
0 3882
33.3%
1 2453
21.1%
2 956
 
8.2%
3 473
 
4.1%

Violation Detail - 6
Text

Missing 

Distinct280
Distinct (%)7.4%
Missing6872
Missing (%)64.4%
Memory size1.9 MiB
2025-04-14T23:24:03.372881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length910
Median length666
Mean length341.6827
Min length125

Characters and Unicode

Total characters1299761
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)2.3%

Sample

1st rowCh.19-126.5(c)) A producer shall sign the manifest from the transporter when a load is picked up by the transporter and shall keep a copy of all trip tickets at the producer#s business office for three years. The director may inspect these records at any reasonable time.
2nd row228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (d) Wiping cloths, use limitation. (2) cloths in-use for wiping counters and other equipment surfaces shall be: (A) held between uses in a chemical sanitizer solution at a concentration specified in õ228.111(n) of this title; and
3rd row228.75 Food. Time and temperature control. (g) Ready-to-eat, TCS food, date marking. (2) Except as specified in paragraphs (5) - (7) of this subsection, refrigerated, ready-to-eat, time/temperature controlled for safety food prepared and packaged by a food processing plant shall be clearly marked, at the time the original container is opened in a food establishment and held at a temperature of 41 degrees Fahrenheit (5 degrees Celsius) or less if the food is held for more than 24 hours, to indicate the date or day by which the food shall be consumed on the premises, sold, or discarded, based on the temperature and time combinations specified in paragraph (1) of this subsection: (A) the day the original container is opened in the food establishment shall be counted as day 1; and
4th row228.108 Equipment, Utensils, and Linens. Utensils, temperature measuring devices, and testing devices. (e) Sanitizing solutions, testing device. A test kit or other device that accurately measures the concentration in mg/L of sanitizing solutions shall be provided.
5th row228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (e) Gloves, use limitation. (1) If used, single-use gloves shall be used for only one task such as working with ready-to-eat food or with raw animal food, used for no other purpose, and discarded when damaged or soiled, or when interruptions occur in the operation.
ValueCountFrequency (%)
and 9908
 
5.6%
food 6953
 
3.9%
of 6445
 
3.6%
the 5555
 
3.1%
a 4893
 
2.8%
shall 4215
 
2.4%
equipment 4117
 
2.3%
in 3846
 
2.2%
be 3800
 
2.1%
or 2934
 
1.7%
Other values (1702) 124373
70.3%
2025-04-14T23:24:03.974494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
266549
20.5%
e 109486
 
8.4%
i 77095
 
5.9%
n 76490
 
5.9%
a 74250
 
5.7%
t 72899
 
5.6%
s 71156
 
5.5%
o 69318
 
5.3%
r 50912
 
3.9%
d 42803
 
3.3%
Other values (62) 388803
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1299761
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
266549
20.5%
e 109486
 
8.4%
i 77095
 
5.9%
n 76490
 
5.9%
a 74250
 
5.7%
t 72899
 
5.6%
s 71156
 
5.5%
o 69318
 
5.3%
r 50912
 
3.9%
d 42803
 
3.3%
Other values (62) 388803
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1299761
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
266549
20.5%
e 109486
 
8.4%
i 77095
 
5.9%
n 76490
 
5.9%
a 74250
 
5.7%
t 72899
 
5.6%
s 71156
 
5.5%
o 69318
 
5.3%
r 50912
 
3.9%
d 42803
 
3.3%
Other values (62) 388803
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1299761
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
266549
20.5%
e 109486
 
8.4%
i 77095
 
5.9%
n 76490
 
5.9%
a 74250
 
5.7%
t 72899
 
5.6%
s 71156
 
5.5%
o 69318
 
5.3%
r 50912
 
3.9%
d 42803
 
3.3%
Other values (62) 388803
29.9%

Violation Memo - 6
Text

Missing 

Distinct3070
Distinct (%)90.0%
Missing7264
Missing (%)68.0%
Memory size575.0 KiB
2025-04-14T23:24:04.403018image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length845
Median length173
Mean length47.357562
Min length3

Characters and Unicode

Total characters161584
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2901 ?
Unique (%)85.0%

Sample

1st rowprovide grease trap ticket
2nd rowno date marking on items in ric
3rd rowprovide sanitizer test strips
4th rowprovide label for food storage containers/common name of food products
5th rowrepair loose frp walls and falling ceiling tile
ValueCountFrequency (%)
in 918
 
3.4%
food 710
 
2.6%
clean 646
 
2.4%
on 526
 
1.9%
observed 477
 
1.8%
and 439
 
1.6%
provide 413
 
1.5%
of 381
 
1.4%
to 352
 
1.3%
the 326
 
1.2%
Other values (2216) 21962
80.9%
2025-04-14T23:24:05.125595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24390
 
15.1%
e 12802
 
7.9%
o 9311
 
5.8%
n 7713
 
4.8%
a 7434
 
4.6%
r 7388
 
4.6%
i 7095
 
4.4%
t 6898
 
4.3%
s 6740
 
4.2%
l 5054
 
3.1%
Other values (73) 66759
41.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 161584
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
24390
 
15.1%
e 12802
 
7.9%
o 9311
 
5.8%
n 7713
 
4.8%
a 7434
 
4.6%
r 7388
 
4.6%
i 7095
 
4.4%
t 6898
 
4.3%
s 6740
 
4.2%
l 5054
 
3.1%
Other values (73) 66759
41.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 161584
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
24390
 
15.1%
e 12802
 
7.9%
o 9311
 
5.8%
n 7713
 
4.8%
a 7434
 
4.6%
r 7388
 
4.6%
i 7095
 
4.4%
t 6898
 
4.3%
s 6740
 
4.2%
l 5054
 
3.1%
Other values (73) 66759
41.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 161584
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
24390
 
15.1%
e 12802
 
7.9%
o 9311
 
5.8%
n 7713
 
4.8%
a 7434
 
4.6%
r 7388
 
4.6%
i 7095
 
4.4%
t 6898
 
4.3%
s 6740
 
4.2%
l 5054
 
3.1%
Other values (73) 66759
41.3%
Distinct249
Distinct (%)8.1%
Missing7608
Missing (%)71.3%
Memory size546.4 KiB
2025-04-14T23:24:05.557467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length80
Mean length44.845502
Min length12

Characters and Unicode

Total characters137586
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)2.3%

Sample

1st row*42 Floors/walls/ceiling/nonfood dirty
2nd row*47 Conditions of Permit-in use of food equipment
3rd row*39 Store equipment & utensils in a clean, dry place
4th row*45 Lockers to be used to store personal items
5th row*47 Conditions of Permit-in use of food equipment
ValueCountFrequency (%)
food 863
 
4.0%
574
 
2.6%
in 432
 
2.0%
or 355
 
1.6%
42 324
 
1.5%
45 312
 
1.4%
dirty 302
 
1.4%
the 292
 
1.3%
be 274
 
1.3%
good 269
 
1.2%
Other values (703) 17671
81.6%
2025-04-14T23:24:06.432748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18972
13.8%
e 11111
 
8.1%
o 10021
 
7.3%
i 8808
 
6.4%
n 8566
 
6.2%
t 7938
 
5.8%
s 7213
 
5.2%
a 6941
 
5.0%
r 6644
 
4.8%
d 4886
 
3.6%
Other values (68) 46486
33.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 137586
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
18972
13.8%
e 11111
 
8.1%
o 10021
 
7.3%
i 8808
 
6.4%
n 8566
 
6.2%
t 7938
 
5.8%
s 7213
 
5.2%
a 6941
 
5.0%
r 6644
 
4.8%
d 4886
 
3.6%
Other values (68) 46486
33.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 137586
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
18972
13.8%
e 11111
 
8.1%
o 10021
 
7.3%
i 8808
 
6.4%
n 8566
 
6.2%
t 7938
 
5.8%
s 7213
 
5.2%
a 6941
 
5.0%
r 6644
 
4.8%
d 4886
 
3.6%
Other values (68) 46486
33.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 137586
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
18972
13.8%
e 11111
 
8.1%
o 10021
 
7.3%
i 8808
 
6.4%
n 8566
 
6.2%
t 7938
 
5.8%
s 7213
 
5.2%
a 6941
 
5.0%
r 6644
 
4.8%
d 4886
 
3.6%
Other values (68) 46486
33.8%

Violation Points - 7
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.1%
Missing7608
Missing (%)71.3%
Memory size655.4 KiB
1.0
2005 
2.0
631 
3.0
432 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9204
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 2005
 
18.8%
2.0 631
 
5.9%
3.0 432
 
4.0%
(Missing) 7608
71.3%

Length

2025-04-14T23:24:06.611763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:06.746545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 2005
65.4%
2.0 631
 
20.6%
3.0 432
 
14.1%

Most occurring characters

ValueCountFrequency (%)
. 3068
33.3%
0 3068
33.3%
1 2005
21.8%
2 631
 
6.9%
3 432
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9204
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 3068
33.3%
0 3068
33.3%
1 2005
21.8%
2 631
 
6.9%
3 432
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9204
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 3068
33.3%
0 3068
33.3%
1 2005
21.8%
2 631
 
6.9%
3 432
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9204
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 3068
33.3%
0 3068
33.3%
1 2005
21.8%
2 631
 
6.9%
3 432
 
4.7%

Violation Detail - 7
Text

Missing 

Distinct253
Distinct (%)8.5%
Missing7688
Missing (%)72.0%
Memory size1.5 MiB
2025-04-14T23:24:07.247037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1018
Median length666
Mean length339.87249
Min length125

Characters and Unicode

Total characters1015539
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)2.3%

Sample

1st row228.114 Equipment, Utensils, and Linens. Frequency of cleaning. (c) Nonfood-contact surfaces. Nonfood-contact surfaces of equipment shall be cleaned at a frequency necessary to preclude accumulation of soil residues.
2nd row228.248 Compliance Conditions of retention, responsibilities of the permit holder. Upon acceptance of the permit issued by the regulatory authority, the permit holder in order to retain the permit shall: (11) Notify customers that a copy of the most recent establishment inspection report is available upon request by posting a sign or placard in a location in the food establishment that is conspicuous to customers or by another method acceptable to the regulatory authority.
3rd row228.124 Equipment, Utensils, and Linens. Storage. (a) Equipment, utensils, linens, and single-service and single-use articles. (1) Except as specified in paragraph (4) of this subsection, cleaned equipment and utensils, laundered linens, and single-service and single-use articles shall be stored: (A) in a clean, dry location;
4th row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (j) Using dressing rooms and lockers. (2) Lockers or other suitable facilities shall be used for the orderly storage of employee clothing and other possessions.
5th row228.248 Compliance Conditions of retention, responsibilities of the permit holder. Upon acceptance of the permit issued by the regulatory authority, the permit holder in order to retain the permit shall: (11) Notify customers that a copy of the most recent establishment inspection report is available upon request by posting a sign or placard in a location in the food establishment that is conspicuous to customers or by another method acceptable to the regulatory authority.
ValueCountFrequency (%)
and 7749
 
5.6%
food 5351
 
3.9%
of 4826
 
3.5%
the 4439
 
3.2%
a 3845
 
2.8%
shall 3350
 
2.4%
equipment 3207
 
2.3%
in 2970
 
2.1%
be 2950
 
2.1%
or 2320
 
1.7%
Other values (1638) 97491
70.4%
2025-04-14T23:24:07.907068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
208520
20.5%
e 86046
 
8.5%
i 60390
 
5.9%
n 59879
 
5.9%
a 58138
 
5.7%
t 56521
 
5.6%
s 56090
 
5.5%
o 53712
 
5.3%
r 39722
 
3.9%
d 33244
 
3.3%
Other values (61) 303277
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1015539
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
208520
20.5%
e 86046
 
8.5%
i 60390
 
5.9%
n 59879
 
5.9%
a 58138
 
5.7%
t 56521
 
5.6%
s 56090
 
5.5%
o 53712
 
5.3%
r 39722
 
3.9%
d 33244
 
3.3%
Other values (61) 303277
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1015539
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
208520
20.5%
e 86046
 
8.5%
i 60390
 
5.9%
n 59879
 
5.9%
a 58138
 
5.7%
t 56521
 
5.6%
s 56090
 
5.5%
o 53712
 
5.3%
r 39722
 
3.9%
d 33244
 
3.3%
Other values (61) 303277
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1015539
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
208520
20.5%
e 86046
 
8.5%
i 60390
 
5.9%
n 59879
 
5.9%
a 58138
 
5.7%
t 56521
 
5.6%
s 56090
 
5.5%
o 53712
 
5.3%
r 39722
 
3.9%
d 33244
 
3.3%
Other values (61) 303277
29.9%

Violation Memo - 7
Text

Missing 

Distinct2403
Distinct (%)89.4%
Missing7988
Missing (%)74.8%
Memory size526.5 KiB
2025-04-14T23:24:08.404683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1837
Median length157
Mean length48.376488
Min length3

Characters and Unicode

Total characters130036
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2291 ?
Unique (%)85.2%

Sample

1st rowCLEAN TOP OF EQUIPMENTS AND STORAGE RACKS
2nd rowprovide sign about inspection report
3rd rowice scoop
4th rowprovide sign about inspection report
5th rowpost
ValueCountFrequency (%)
in 754
 
3.5%
food 543
 
2.5%
clean 471
 
2.2%
on 379
 
1.8%
observed 344
 
1.6%
provide 343
 
1.6%
and 343
 
1.6%
all 282
 
1.3%
to 276
 
1.3%
at 276
 
1.3%
Other values (1950) 17616
81.5%
2025-04-14T23:24:09.105938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20129
 
15.5%
e 10181
 
7.8%
o 7434
 
5.7%
n 6363
 
4.9%
a 6074
 
4.7%
r 5794
 
4.5%
i 5781
 
4.4%
s 5567
 
4.3%
t 5517
 
4.2%
l 4118
 
3.2%
Other values (73) 53078
40.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 130036
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
20129
 
15.5%
e 10181
 
7.8%
o 7434
 
5.7%
n 6363
 
4.9%
a 6074
 
4.7%
r 5794
 
4.5%
i 5781
 
4.4%
s 5567
 
4.3%
t 5517
 
4.2%
l 4118
 
3.2%
Other values (73) 53078
40.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 130036
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
20129
 
15.5%
e 10181
 
7.8%
o 7434
 
5.7%
n 6363
 
4.9%
a 6074
 
4.7%
r 5794
 
4.5%
i 5781
 
4.4%
s 5567
 
4.3%
t 5517
 
4.2%
l 4118
 
3.2%
Other values (73) 53078
40.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 130036
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
20129
 
15.5%
e 10181
 
7.8%
o 7434
 
5.7%
n 6363
 
4.9%
a 6074
 
4.7%
r 5794
 
4.5%
i 5781
 
4.4%
s 5567
 
4.3%
t 5517
 
4.2%
l 4118
 
3.2%
Other values (73) 53078
40.8%
Distinct228
Distinct (%)9.6%
Missing8311
Missing (%)77.8%
Memory size499.9 KiB
2025-04-14T23:24:09.302860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length80
Mean length45.793658
Min length12

Characters and Unicode

Total characters108302
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)2.8%

Sample

1st row*36 Containers of chemical sanitizing solutions stored off the floor and used in a manner that preve
2nd row*35 Eating food, chewing gum, drinking beverages, or using tobacco
3rd row*36 Cloths in-use for wiping between uses stored
4th row*42 Dirty nonfood contact surfaces
5th row*41 Food storage containers, identified with common name of food.
ValueCountFrequency (%)
food 724
 
4.3%
408
 
2.4%
in 354
 
2.1%
42 271
 
1.6%
the 257
 
1.5%
dirty 256
 
1.5%
or 255
 
1.5%
of 247
 
1.5%
good 215
 
1.3%
45 208
 
1.2%
Other values (644) 13785
81.2%
2025-04-14T23:24:09.645859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14893
13.8%
e 8637
 
8.0%
o 8178
 
7.6%
i 6882
 
6.4%
n 6813
 
6.3%
t 6363
 
5.9%
s 5734
 
5.3%
a 5492
 
5.1%
r 5123
 
4.7%
d 3884
 
3.6%
Other values (67) 36303
33.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 108302
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
14893
13.8%
e 8637
 
8.0%
o 8178
 
7.6%
i 6882
 
6.4%
n 6813
 
6.3%
t 6363
 
5.9%
s 5734
 
5.3%
a 5492
 
5.1%
r 5123
 
4.7%
d 3884
 
3.6%
Other values (67) 36303
33.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 108302
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
14893
13.8%
e 8637
 
8.0%
o 8178
 
7.6%
i 6882
 
6.4%
n 6813
 
6.3%
t 6363
 
5.9%
s 5734
 
5.3%
a 5492
 
5.1%
r 5123
 
4.7%
d 3884
 
3.6%
Other values (67) 36303
33.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 108302
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
14893
13.8%
e 8637
 
8.0%
o 8178
 
7.6%
i 6882
 
6.4%
n 6813
 
6.3%
t 6363
 
5.9%
s 5734
 
5.3%
a 5492
 
5.1%
r 5123
 
4.7%
d 3884
 
3.6%
Other values (67) 36303
33.5%

Violation Points - 8
Categorical

Missing 

Distinct3
Distinct (%)0.1%
Missing8311
Missing (%)77.8%
Memory size658.1 KiB
1.0
1543 
2.0
505 
3.0
317 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters7095
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 1543
 
14.5%
2.0 505
 
4.7%
3.0 317
 
3.0%
(Missing) 8311
77.8%

Length

2025-04-14T23:24:09.748081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:09.812968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 1543
65.2%
2.0 505
 
21.4%
3.0 317
 
13.4%

Most occurring characters

ValueCountFrequency (%)
. 2365
33.3%
0 2365
33.3%
1 1543
21.7%
2 505
 
7.1%
3 317
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7095
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 2365
33.3%
0 2365
33.3%
1 1543
21.7%
2 505
 
7.1%
3 317
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7095
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 2365
33.3%
0 2365
33.3%
1 1543
21.7%
2 505
 
7.1%
3 317
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7095
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 2365
33.3%
0 2365
33.3%
1 1543
21.7%
2 505
 
7.1%
3 317
 
4.5%

Violation Detail - 8
Text

Missing 

Distinct231
Distinct (%)10.0%
Missing8372
Missing (%)78.4%
Memory size1.3 MiB
2025-04-14T23:24:10.164636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length829
Median length617
Mean length342.05295
Min length125

Characters and Unicode

Total characters788090
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)2.9%

Sample

1st row228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (d) Wiping cloths, use limitation. (5) containers of chemical sanitizing solutions specified in paragraph (2)(A) of this subsection in which wet wiping cloths are held between uses shall be stored off the floor and used in a manner that prevents contamination of food, equipment, utensils, linens, single-service, or single-use articles. .
2nd row228.42 Management and Personnel. Food Contamination Prevention (a) Eating, drinking, or using tobacco. (1) except as specified in paragraph (2) of this subsection, an employee shall eat, drink, or use any form of tobacco only in designated areas where the contamination of exposed food; clean equipment, utensils, and linens; unwrapped single-service and single-use articles; or other items needing protection cannot result.
3rd row228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (d) Wiping cloths, use limitation. (2) cloths in-use for wiping counters and other equipment surfaces shall be: (A) held between uses in a chemical sanitizer solution at a concentration specified in õ228.111(n) of this title; and
4th row228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.
5th row228.66 Food. Preventing food and ingredient contamination. (b) Food storage containers, identified with common name of food. Except for containers holding food that can be readily and unmistakably recognized such as dry pasta, working containers holding food or food ingredients that are removed from their original packages for use in the food establishment, such as cooking oils, flour, herbs, potato flakes, salt, spices, and sugar shall be identified with the common name of the food.
ValueCountFrequency (%)
and 6047
 
5.6%
food 4489
 
4.2%
of 3887
 
3.6%
the 3360
 
3.1%
a 2841
 
2.6%
shall 2549
 
2.4%
equipment 2384
 
2.2%
in 2351
 
2.2%
be 2336
 
2.2%
or 1749
 
1.6%
Other values (1475) 75504
70.2%
2025-04-14T23:24:10.709397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
161642
20.5%
e 65910
 
8.4%
i 47001
 
6.0%
n 46485
 
5.9%
a 45241
 
5.7%
t 44035
 
5.6%
s 42976
 
5.5%
o 42688
 
5.4%
r 30572
 
3.9%
d 26013
 
3.3%
Other values (61) 235527
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 788090
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
161642
20.5%
e 65910
 
8.4%
i 47001
 
6.0%
n 46485
 
5.9%
a 45241
 
5.7%
t 44035
 
5.6%
s 42976
 
5.5%
o 42688
 
5.4%
r 30572
 
3.9%
d 26013
 
3.3%
Other values (61) 235527
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 788090
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
161642
20.5%
e 65910
 
8.4%
i 47001
 
6.0%
n 46485
 
5.9%
a 45241
 
5.7%
t 44035
 
5.6%
s 42976
 
5.5%
o 42688
 
5.4%
r 30572
 
3.9%
d 26013
 
3.3%
Other values (61) 235527
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 788090
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
161642
20.5%
e 65910
 
8.4%
i 47001
 
6.0%
n 46485
 
5.9%
a 45241
 
5.7%
t 44035
 
5.6%
s 42976
 
5.5%
o 42688
 
5.4%
r 30572
 
3.9%
d 26013
 
3.3%
Other values (61) 235527
29.9%

Violation Memo - 8
Text

Missing 

Distinct1899
Distinct (%)90.7%
Missing8582
Missing (%)80.4%
Memory size483.2 KiB
2025-04-14T23:24:11.078784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1516
Median length141
Mean length47.998567
Min length3

Characters and Unicode

Total characters100509
Distinct characters84
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1805 ?
Unique (%)86.2%

Sample

1st rowsanitizer bucket sit on floor
2nd rowpersonal food separate from kids food
3rd rowclean coolers inside, shelves, gaskets, clean pipe under 3 com sink
4th rowLABEL SQUEEZE BOTTLE THAT HAVE OIL/BUTTER.
5th rowprovide sign about inspection report
ValueCountFrequency (%)
in 556
 
3.3%
food 441
 
2.6%
clean 398
 
2.4%
observed 275
 
1.6%
on 273
 
1.6%
provide 257
 
1.5%
and 241
 
1.4%
all 226
 
1.4%
of 216
 
1.3%
at 213
 
1.3%
Other values (1745) 13591
81.4%
2025-04-14T23:24:11.619637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15358
 
15.3%
e 7945
 
7.9%
o 5760
 
5.7%
n 4799
 
4.8%
a 4707
 
4.7%
r 4479
 
4.5%
s 4380
 
4.4%
i 4362
 
4.3%
t 4163
 
4.1%
l 3213
 
3.2%
Other values (74) 41343
41.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 100509
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
15358
 
15.3%
e 7945
 
7.9%
o 5760
 
5.7%
n 4799
 
4.8%
a 4707
 
4.7%
r 4479
 
4.5%
s 4380
 
4.4%
i 4362
 
4.3%
t 4163
 
4.1%
l 3213
 
3.2%
Other values (74) 41343
41.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 100509
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
15358
 
15.3%
e 7945
 
7.9%
o 5760
 
5.7%
n 4799
 
4.8%
a 4707
 
4.7%
r 4479
 
4.5%
s 4380
 
4.4%
i 4362
 
4.3%
t 4163
 
4.1%
l 3213
 
3.2%
Other values (74) 41343
41.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 100509
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
15358
 
15.3%
e 7945
 
7.9%
o 5760
 
5.7%
n 4799
 
4.8%
a 4707
 
4.7%
r 4479
 
4.5%
s 4380
 
4.4%
i 4362
 
4.3%
t 4163
 
4.1%
l 3213
 
3.2%
Other values (74) 41343
41.1%
Distinct213
Distinct (%)11.8%
Missing8871
Missing (%)83.1%
Memory size457.4 KiB
2025-04-14T23:24:11.805734image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length80
Mean length44.307479
Min length13

Characters and Unicode

Total characters79975
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)4.3%

Sample

1st row*14 When to wash hands between raw and RTE foods
2nd row*35 Eating food, chewing gum, drinking beverages, or using tobacco
3rd row*29 Sanitizing solutions, testing devices
4th row*28 Date marking > 24 hrs,on site,temp 41F
5th row*20 Grease Trap Tickets
ValueCountFrequency (%)
food 506
 
4.1%
327
 
2.6%
in 265
 
2.1%
42 208
 
1.7%
dirty 199
 
1.6%
of 183
 
1.5%
repair 180
 
1.5%
good 177
 
1.4%
45 173
 
1.4%
be 164
 
1.3%
Other values (611) 10015
80.8%
2025-04-14T23:24:12.130876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10830
13.5%
e 6371
 
8.0%
o 5911
 
7.4%
i 5299
 
6.6%
n 5021
 
6.3%
t 4655
 
5.8%
s 4223
 
5.3%
a 4046
 
5.1%
r 3825
 
4.8%
d 2858
 
3.6%
Other values (69) 26936
33.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 79975
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
10830
13.5%
e 6371
 
8.0%
o 5911
 
7.4%
i 5299
 
6.6%
n 5021
 
6.3%
t 4655
 
5.8%
s 4223
 
5.3%
a 4046
 
5.1%
r 3825
 
4.8%
d 2858
 
3.6%
Other values (69) 26936
33.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 79975
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
10830
13.5%
e 6371
 
8.0%
o 5911
 
7.4%
i 5299
 
6.6%
n 5021
 
6.3%
t 4655
 
5.8%
s 4223
 
5.3%
a 4046
 
5.1%
r 3825
 
4.8%
d 2858
 
3.6%
Other values (69) 26936
33.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 79975
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
10830
13.5%
e 6371
 
8.0%
o 5911
 
7.4%
i 5299
 
6.6%
n 5021
 
6.3%
t 4655
 
5.8%
s 4223
 
5.3%
a 4046
 
5.1%
r 3825
 
4.8%
d 2858
 
3.6%
Other values (69) 26936
33.7%

Violation Points - 9
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.2%
Missing8871
Missing (%)83.1%
Memory size660.3 KiB
1.0
1178 
2.0
391 
3.0
236 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters5415
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3.0
2nd row1.0
3rd row2.0
4th row2.0
5th row3.0

Common Values

ValueCountFrequency (%)
1.0 1178
 
11.0%
2.0 391
 
3.7%
3.0 236
 
2.2%
(Missing) 8871
83.1%

Length

2025-04-14T23:24:12.246012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:12.314567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 1178
65.3%
2.0 391
 
21.7%
3.0 236
 
13.1%

Most occurring characters

ValueCountFrequency (%)
. 1805
33.3%
0 1805
33.3%
1 1178
21.8%
2 391
 
7.2%
3 236
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5415
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 1805
33.3%
0 1805
33.3%
1 1178
21.8%
2 391
 
7.2%
3 236
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5415
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 1805
33.3%
0 1805
33.3%
1 1178
21.8%
2 391
 
7.2%
3 236
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5415
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 1805
33.3%
0 1805
33.3%
1 1178
21.8%
2 391
 
7.2%
3 236
 
4.4%

Violation Detail - 9
Text

Missing 

Distinct216
Distinct (%)12.3%
Missing8917
Missing (%)83.5%
Memory size1.0 MiB
2025-04-14T23:24:12.623979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length910
Median length639
Mean length340.60773
Min length125

Characters and Unicode

Total characters599129
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)4.5%

Sample

1st row228.38 Management and Personnel. (d) When to wash. Food employees shall clean their hands and exposed portions of their arms as specified in subsection (b) of this section immediately before engaging in food preparation including working with exposed food, clean equipment and utensils, and unwrapped single-service and single-use articles and: (7) when switching between working with raw food and working with ready-to eat food;
2nd row228.42 Management and Personnel. Food Contamination Prevention (a) Eating, drinking, or using tobacco. (1) except as specified in paragraph (2) of this subsection, an employee shall eat, drink, or use any form of tobacco only in designated areas where the contamination of exposed food; clean equipment, utensils, and linens; unwrapped single-service and single-use articles; or other items needing protection cannot result.
3rd row228.108 Equipment, Utensils, and Linens. Utensils, temperature measuring devices, and testing devices. (e) Sanitizing solutions, testing device. A test kit or other device that accurately measures the concentration in mg/L of sanitizing solutions shall be provided.
4th row228.75 Food. Time and temperature control. (g) Ready-to-eat, TCS food, date marking. (2) Except as specified in paragraphs (5) - (7) of this subsection, refrigerated, ready-to-eat, time/temperature controlled for safety food prepared and packaged by a food processing plant shall be clearly marked, at the time the original container is opened in a food establishment and held at a temperature of 41 degrees Fahrenheit (5 degrees Celsius) or less if the food is held for more than 24 hours, to indicate the date or day by which the food shall be consumed on the premises, sold, or discarded, based on the temperature and time combinations specified in paragraph (1) of this subsection: (A) the day the original container is opened in the food establishment shall be counted as day 1; and
5th rowCh.19-126.5(c)) A producer shall sign the manifest from the transporter when a load is picked up by the transporter and shall keep a copy of all trip tickets at the producer#s business office for three years. The director may inspect these records at any reasonable time.
ValueCountFrequency (%)
and 4570
 
5.6%
food 3230
 
4.0%
of 2938
 
3.6%
the 2609
 
3.2%
a 2195
 
2.7%
shall 1941
 
2.4%
equipment 1845
 
2.3%
be 1765
 
2.2%
in 1719
 
2.1%
or 1309
 
1.6%
Other values (1502) 57545
70.5%
2025-04-14T23:24:13.615683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122252
20.4%
e 50638
 
8.5%
i 36352
 
6.1%
n 35183
 
5.9%
a 34303
 
5.7%
t 33216
 
5.5%
s 33104
 
5.5%
o 31678
 
5.3%
r 23356
 
3.9%
d 19815
 
3.3%
Other values (62) 179232
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 599129
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
122252
20.4%
e 50638
 
8.5%
i 36352
 
6.1%
n 35183
 
5.9%
a 34303
 
5.7%
t 33216
 
5.5%
s 33104
 
5.5%
o 31678
 
5.3%
r 23356
 
3.9%
d 19815
 
3.3%
Other values (62) 179232
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 599129
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
122252
20.4%
e 50638
 
8.5%
i 36352
 
6.1%
n 35183
 
5.9%
a 34303
 
5.7%
t 33216
 
5.5%
s 33104
 
5.5%
o 31678
 
5.3%
r 23356
 
3.9%
d 19815
 
3.3%
Other values (62) 179232
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 599129
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
122252
20.4%
e 50638
 
8.5%
i 36352
 
6.1%
n 35183
 
5.9%
a 34303
 
5.7%
t 33216
 
5.5%
s 33104
 
5.5%
o 31678
 
5.3%
r 23356
 
3.9%
d 19815
 
3.3%
Other values (62) 179232
29.9%

Violation Memo - 9
Text

Missing 

Distinct1452
Distinct (%)90.8%
Missing9077
Missing (%)85.0%
Memory size446.5 KiB
2025-04-14T23:24:13.976144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length845
Median length138
Mean length47.14384
Min length4

Characters and Unicode

Total characters75383
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1380 ?
Unique (%)86.3%

Sample

1st rowdid not wash hands after touching raw chicken
2nd rowpersona water bottle (open) sit on shelve in reach in cooler
3rd rowsanitizer test strips
4th rowmaintain up to date grease trap
5th rowProvide thermometers for all food cooler and freezers
ValueCountFrequency (%)
in 389
 
3.1%
food 339
 
2.7%
clean 313
 
2.5%
on 214
 
1.7%
observed 210
 
1.7%
provide 202
 
1.6%
and 202
 
1.6%
of 162
 
1.3%
sink 156
 
1.2%
to 151
 
1.2%
Other values (1541) 10221
81.4%
2025-04-14T23:24:14.497808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11302
 
15.0%
e 6229
 
8.3%
o 4465
 
5.9%
n 3676
 
4.9%
a 3636
 
4.8%
r 3580
 
4.7%
i 3423
 
4.5%
s 3362
 
4.5%
t 3198
 
4.2%
l 2470
 
3.3%
Other values (73) 30042
39.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 75383
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
11302
 
15.0%
e 6229
 
8.3%
o 4465
 
5.9%
n 3676
 
4.9%
a 3636
 
4.8%
r 3580
 
4.7%
i 3423
 
4.5%
s 3362
 
4.5%
t 3198
 
4.2%
l 2470
 
3.3%
Other values (73) 30042
39.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 75383
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
11302
 
15.0%
e 6229
 
8.3%
o 4465
 
5.9%
n 3676
 
4.9%
a 3636
 
4.8%
r 3580
 
4.7%
i 3423
 
4.5%
s 3362
 
4.5%
t 3198
 
4.2%
l 2470
 
3.3%
Other values (73) 30042
39.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 75383
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
11302
 
15.0%
e 6229
 
8.3%
o 4465
 
5.9%
n 3676
 
4.9%
a 3636
 
4.8%
r 3580
 
4.7%
i 3423
 
4.5%
s 3362
 
4.5%
t 3198
 
4.2%
l 2470
 
3.3%
Other values (73) 30042
39.9%
Distinct193
Distinct (%)14.8%
Missing9368
Missing (%)87.7%
Memory size424.5 KiB
2025-04-14T23:24:14.812094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length84
Mean length45.074924
Min length12

Characters and Unicode

Total characters58958
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)5.4%

Sample

1st row*37 Storing the food at least 15 cm (6 inches) above the floor
2nd row*34 Pest control-routine inspections for
3rd row*35 Eating food, chewing gum, drinking beverages, or using tobacco
4th row*30 Food Establishment Permit
5th row*46 Covered waste receptacle for women's restroom
ValueCountFrequency (%)
food 391
 
4.2%
220
 
2.4%
in 202
 
2.2%
42 145
 
1.6%
dirty 137
 
1.5%
45 131
 
1.4%
or 129
 
1.4%
good 127
 
1.4%
repair 124
 
1.3%
be 120
 
1.3%
Other values (581) 7499
81.3%
2025-04-14T23:24:15.280925image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8084
13.7%
e 4852
 
8.2%
o 4300
 
7.3%
i 3765
 
6.4%
n 3637
 
6.2%
t 3385
 
5.7%
s 3184
 
5.4%
a 2983
 
5.1%
r 2844
 
4.8%
d 2110
 
3.6%
Other values (67) 19814
33.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 58958
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8084
13.7%
e 4852
 
8.2%
o 4300
 
7.3%
i 3765
 
6.4%
n 3637
 
6.2%
t 3385
 
5.7%
s 3184
 
5.4%
a 2983
 
5.1%
r 2844
 
4.8%
d 2110
 
3.6%
Other values (67) 19814
33.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 58958
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8084
13.7%
e 4852
 
8.2%
o 4300
 
7.3%
i 3765
 
6.4%
n 3637
 
6.2%
t 3385
 
5.7%
s 3184
 
5.4%
a 2983
 
5.1%
r 2844
 
4.8%
d 2110
 
3.6%
Other values (67) 19814
33.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 58958
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8084
13.7%
e 4852
 
8.2%
o 4300
 
7.3%
i 3765
 
6.4%
n 3637
 
6.2%
t 3385
 
5.7%
s 3184
 
5.4%
a 2983
 
5.1%
r 2844
 
4.8%
d 2110
 
3.6%
Other values (67) 19814
33.6%

Violation Points - 10
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.2%
Missing9368
Missing (%)87.7%
Memory size662.3 KiB
1.0
842 
2.0
271 
3.0
195 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3924
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row2.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 842
 
7.9%
2.0 271
 
2.5%
3.0 195
 
1.8%
(Missing) 9368
87.7%

Length

2025-04-14T23:24:15.393039image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:15.463665image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 842
64.4%
2.0 271
 
20.7%
3.0 195
 
14.9%

Most occurring characters

ValueCountFrequency (%)
. 1308
33.3%
0 1308
33.3%
1 842
21.5%
2 271
 
6.9%
3 195
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3924
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 1308
33.3%
0 1308
33.3%
1 842
21.5%
2 271
 
6.9%
3 195
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3924
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 1308
33.3%
0 1308
33.3%
1 842
21.5%
2 271
 
6.9%
3 195
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3924
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 1308
33.3%
0 1308
33.3%
1 842
21.5%
2 271
 
6.9%
3 195
 
5.0%

Violation Detail - 10
Text

Missing 

Distinct195
Distinct (%)15.2%
Missing9394
Missing (%)88.0%
Memory size853.8 KiB
2025-04-14T23:24:15.783585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length888
Median length575
Mean length341.20203
Min length125

Characters and Unicode

Total characters437421
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)5.8%

Sample

1st row228.69 Food. Preventing contamination from the premises. (a) Food Storage. (1) Except as specified in paragraphs (2) and (3) of this subsection, food shall be protected from contamination by storing the food: (C) at least 15 centimeters (6 inches) above the floor.
2nd row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (k) Controlling pests. The presence of insects, rodents, and other pests shall be controlled to minimize their presence within the physical facility and its contents, and on the contiguous land or property under the control of the permit holder by: (2) routinely inspecting the premises for evidence of pests;
3rd row228.42 Management and Personnel. Food Contamination Prevention (a) Eating, drinking, or using tobacco. (1) except as specified in paragraph (2) of this subsection, an employee shall eat, drink, or use any form of tobacco only in designated areas where the contamination of exposed food; clean equipment, utensils, and linens; unwrapped single-service and single-use articles; or other items needing protection cannot result.
4th rowSEC. 17-10.2. ADDITIONAL REQUIREMENTS. (c) Permits. (1) Requisite. A person shall not operate a food establishment inside the city without a permit issued by the director. A separate permit is required for: (A) each establishment that is under a separate ownership;
5th row228.152 Water, Plumbing, and Waste. Refuse, Recyclables, and Returnables, Facilities on the Premises. (h) Toilet room receptacle, covered. A toilet room used by females shall be provided with a covered receptacle for sanitary napkins.
ValueCountFrequency (%)
and 3282
 
5.5%
food 2426
 
4.0%
of 2060
 
3.4%
the 1977
 
3.3%
a 1683
 
2.8%
shall 1421
 
2.4%
be 1279
 
2.1%
in 1276
 
2.1%
equipment 1265
 
2.1%
or 964
 
1.6%
Other values (1339) 42397
70.6%
2025-04-14T23:24:16.307164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89475
20.5%
e 37035
 
8.5%
i 26191
 
6.0%
a 25345
 
5.8%
n 25333
 
5.8%
t 24396
 
5.6%
s 23886
 
5.5%
o 23359
 
5.3%
r 17286
 
4.0%
d 14579
 
3.3%
Other values (61) 130536
29.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 437421
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
89475
20.5%
e 37035
 
8.5%
i 26191
 
6.0%
a 25345
 
5.8%
n 25333
 
5.8%
t 24396
 
5.6%
s 23886
 
5.5%
o 23359
 
5.3%
r 17286
 
4.0%
d 14579
 
3.3%
Other values (61) 130536
29.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 437421
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
89475
20.5%
e 37035
 
8.5%
i 26191
 
6.0%
a 25345
 
5.8%
n 25333
 
5.8%
t 24396
 
5.6%
s 23886
 
5.5%
o 23359
 
5.3%
r 17286
 
4.0%
d 14579
 
3.3%
Other values (61) 130536
29.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 437421
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
89475
20.5%
e 37035
 
8.5%
i 26191
 
6.0%
a 25345
 
5.8%
n 25333
 
5.8%
t 24396
 
5.6%
s 23886
 
5.5%
o 23359
 
5.3%
r 17286
 
4.0%
d 14579
 
3.3%
Other values (61) 130536
29.8%

Violation Memo - 10
Text

Missing 

Distinct1059
Distinct (%)90.7%
Missing9509
Missing (%)89.1%
Memory size419.7 KiB
2025-04-14T23:24:16.601742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1372
Median length137
Mean length50.371894
Min length3

Characters and Unicode

Total characters58784
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1008 ?
Unique (%)86.4%

Sample

1st rowfood needs to be 6 inches above ground
2nd rowobserved flies
3rd rowStore personal food separately, do not store personal items with utensils, Store personal belongings in lockers or designated area
4th rowpost health permit for public view
5th rowprovide covered receptacle in restroom
ValueCountFrequency (%)
in 323
 
3.3%
food 258
 
2.7%
clean 217
 
2.2%
provide 169
 
1.7%
on 153
 
1.6%
observed 151
 
1.6%
and 150
 
1.6%
to 117
 
1.2%
sink 116
 
1.2%
not 114
 
1.2%
Other values (1345) 7902
81.7%
2025-04-14T23:24:17.053771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9016
 
15.3%
e 4658
 
7.9%
o 3463
 
5.9%
n 2879
 
4.9%
a 2833
 
4.8%
r 2708
 
4.6%
s 2606
 
4.4%
i 2596
 
4.4%
t 2515
 
4.3%
l 1909
 
3.2%
Other values (68) 23601
40.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 58784
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9016
 
15.3%
e 4658
 
7.9%
o 3463
 
5.9%
n 2879
 
4.9%
a 2833
 
4.8%
r 2708
 
4.6%
s 2606
 
4.4%
i 2596
 
4.4%
t 2515
 
4.3%
l 1909
 
3.2%
Other values (68) 23601
40.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 58784
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9016
 
15.3%
e 4658
 
7.9%
o 3463
 
5.9%
n 2879
 
4.9%
a 2833
 
4.8%
r 2708
 
4.6%
s 2606
 
4.4%
i 2596
 
4.4%
t 2515
 
4.3%
l 1909
 
3.2%
Other values (68) 23601
40.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 58784
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9016
 
15.3%
e 4658
 
7.9%
o 3463
 
5.9%
n 2879
 
4.9%
a 2833
 
4.8%
r 2708
 
4.6%
s 2606
 
4.4%
i 2596
 
4.4%
t 2515
 
4.3%
l 1909
 
3.2%
Other values (68) 23601
40.1%
Distinct167
Distinct (%)18.4%
Missing9767
Missing (%)91.5%
Memory size397.0 KiB
2025-04-14T23:24:17.256299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length83
Mean length44.918592
Min length16

Characters and Unicode

Total characters40831
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)6.9%

Sample

1st row*46 Covered waste receptacle for women's restroom
2nd row*37 Storing the food at least 15 cm (6 inches) above the floor
3rd row*32 Equipment and Utensils Durability and Strength
4th row*47 Conditions of Permit-in use of food equipment
5th row*36 Cloths in-use for wiping food spills used for no other purpose
ValueCountFrequency (%)
food 279
 
4.4%
149
 
2.3%
in 144
 
2.3%
of 128
 
2.0%
good 104
 
1.6%
repair 101
 
1.6%
45 101
 
1.6%
47 95
 
1.5%
be 92
 
1.4%
equipment 91
 
1.4%
Other values (518) 5098
79.9%
2025-04-14T23:24:17.615887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5601
13.7%
e 3426
 
8.4%
o 2983
 
7.3%
i 2660
 
6.5%
n 2489
 
6.1%
t 2303
 
5.6%
s 2165
 
5.3%
a 2077
 
5.1%
r 1948
 
4.8%
d 1482
 
3.6%
Other values (63) 13697
33.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 40831
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5601
13.7%
e 3426
 
8.4%
o 2983
 
7.3%
i 2660
 
6.5%
n 2489
 
6.1%
t 2303
 
5.6%
s 2165
 
5.3%
a 2077
 
5.1%
r 1948
 
4.8%
d 1482
 
3.6%
Other values (63) 13697
33.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 40831
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5601
13.7%
e 3426
 
8.4%
o 2983
 
7.3%
i 2660
 
6.5%
n 2489
 
6.1%
t 2303
 
5.6%
s 2165
 
5.3%
a 2077
 
5.1%
r 1948
 
4.8%
d 1482
 
3.6%
Other values (63) 13697
33.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 40831
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5601
13.7%
e 3426
 
8.4%
o 2983
 
7.3%
i 2660
 
6.5%
n 2489
 
6.1%
t 2303
 
5.6%
s 2165
 
5.3%
a 2077
 
5.1%
r 1948
 
4.8%
d 1482
 
3.6%
Other values (63) 13697
33.5%

Violation Points - 11
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.3%
Missing9767
Missing (%)91.5%
Memory size663.8 KiB
1.0
605 
2.0
181 
3.0
123 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters2727
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row2.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 605
 
5.7%
2.0 181
 
1.7%
3.0 123
 
1.2%
(Missing) 9767
91.5%

Length

2025-04-14T23:24:17.718285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:17.781812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 605
66.6%
2.0 181
 
19.9%
3.0 123
 
13.5%

Most occurring characters

ValueCountFrequency (%)
. 909
33.3%
0 909
33.3%
1 605
22.2%
2 181
 
6.6%
3 123
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2727
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 909
33.3%
0 909
33.3%
1 605
22.2%
2 181
 
6.6%
3 123
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2727
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 909
33.3%
0 909
33.3%
1 605
22.2%
2 181
 
6.6%
3 123
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2727
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 909
33.3%
0 909
33.3%
1 605
22.2%
2 181
 
6.6%
3 123
 
4.5%

Violation Detail - 11
Text

Missing 

Distinct168
Distinct (%)19.0%
Missing9790
Missing (%)91.7%
Memory size691.1 KiB
2025-04-14T23:24:18.059936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length888
Median length521
Mean length339.23815
Min length148

Characters and Unicode

Total characters300565
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)7.3%

Sample

1st row228.152 Water, Plumbing, and Waste. Refuse, Recyclables, and Returnables, Facilities on the Premises. (h) Toilet room receptacle, covered. A toilet room used by females shall be provided with a covered receptacle for sanitary napkins.
2nd row228.69 Food. Preventing contamination from the premises. (a) Food Storage. (1) Except as specified in paragraphs (2) and (3) of this subsection, food shall be protected from contamination by storing the food: (C) at least 15 centimeters (6 inches) above the floor.
3rd row228.103 Equipment, Utensils, and Linens. Durability and strength. (a) Equipment and utensils. Equipment and utensils shall be designed and constructed to be durable and to retain their characteristic qualities under normal use conditions.
4th row228.248 Compliance Conditions of retention, responsibilities of the permit holder. Upon acceptance of the permit issued by the regulatory authority, the permit holder in order to retain the permit shall: (11) Notify customers that a copy of the most recent establishment inspection report is available upon request by posting a sign or placard in a location in the food establishment that is conspicuous to customers or by another method acceptable to the regulatory authority.
5th row228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (d) Wiping cloths, use limitation. (1) cloths in-use for wiping food spills from tableware and carry-out containers that occur as food is being served shall be: (B) used for no other purpose.
ValueCountFrequency (%)
and 2224
 
5.4%
food 1659
 
4.0%
of 1413
 
3.4%
the 1363
 
3.3%
a 1119
 
2.7%
shall 969
 
2.4%
be 904
 
2.2%
in 868
 
2.1%
equipment 820
 
2.0%
or 671
 
1.6%
Other values (1269) 28955
70.7%
2025-04-14T23:24:18.534689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
61654
20.5%
e 25660
 
8.5%
i 17969
 
6.0%
a 17378
 
5.8%
n 17043
 
5.7%
t 16807
 
5.6%
s 16518
 
5.5%
o 16020
 
5.3%
r 12015
 
4.0%
d 9789
 
3.3%
Other values (62) 89712
29.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 300565
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
61654
20.5%
e 25660
 
8.5%
i 17969
 
6.0%
a 17378
 
5.8%
n 17043
 
5.7%
t 16807
 
5.6%
s 16518
 
5.5%
o 16020
 
5.3%
r 12015
 
4.0%
d 9789
 
3.3%
Other values (62) 89712
29.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 300565
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
61654
20.5%
e 25660
 
8.5%
i 17969
 
6.0%
a 17378
 
5.8%
n 17043
 
5.7%
t 16807
 
5.6%
s 16518
 
5.5%
o 16020
 
5.3%
r 12015
 
4.0%
d 9789
 
3.3%
Other values (62) 89712
29.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 300565
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
61654
20.5%
e 25660
 
8.5%
i 17969
 
6.0%
a 17378
 
5.8%
n 17043
 
5.7%
t 16807
 
5.6%
s 16518
 
5.5%
o 16020
 
5.3%
r 12015
 
4.0%
d 9789
 
3.3%
Other values (62) 89712
29.8%

Violation Memo - 11
Text

Missing 

Distinct743
Distinct (%)91.1%
Missing9860
Missing (%)92.4%
Memory size391.2 KiB
2025-04-14T23:24:18.880664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length604
Median length120
Mean length47.132353
Min length4

Characters and Unicode

Total characters38460
Distinct characters81
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique708 ?
Unique (%)86.8%

Sample

1st rowprovide covered receptacle
2nd rowDo not use canned food as door stopper
3rd rowdo not reuse foil single use containers
4th rowsign about inspection report
5th rowobserved cloth under cutting boards
ValueCountFrequency (%)
in 209
 
3.3%
food 175
 
2.8%
clean 127
 
2.0%
provide 115
 
1.8%
on 96
 
1.5%
of 89
 
1.4%
and 85
 
1.3%
observed 85
 
1.3%
repair 84
 
1.3%
sink 81
 
1.3%
Other values (1051) 5203
81.9%
2025-04-14T23:24:19.585711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5628
 
14.6%
e 3136
 
8.2%
o 2351
 
6.1%
r 1891
 
4.9%
a 1854
 
4.8%
n 1843
 
4.8%
i 1761
 
4.6%
s 1751
 
4.6%
t 1669
 
4.3%
d 1237
 
3.2%
Other values (71) 15339
39.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38460
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5628
 
14.6%
e 3136
 
8.2%
o 2351
 
6.1%
r 1891
 
4.9%
a 1854
 
4.8%
n 1843
 
4.8%
i 1761
 
4.6%
s 1751
 
4.6%
t 1669
 
4.3%
d 1237
 
3.2%
Other values (71) 15339
39.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38460
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5628
 
14.6%
e 3136
 
8.2%
o 2351
 
6.1%
r 1891
 
4.9%
a 1854
 
4.8%
n 1843
 
4.8%
i 1761
 
4.6%
s 1751
 
4.6%
t 1669
 
4.3%
d 1237
 
3.2%
Other values (71) 15339
39.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38460
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5628
 
14.6%
e 3136
 
8.2%
o 2351
 
6.1%
r 1891
 
4.9%
a 1854
 
4.8%
n 1843
 
4.8%
i 1761
 
4.6%
s 1751
 
4.6%
t 1669
 
4.3%
d 1237
 
3.2%
Other values (71) 15339
39.9%
Distinct141
Distinct (%)24.4%
Missing10098
Missing (%)94.6%
Memory size374.4 KiB
2025-04-14T23:24:20.052557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length80
Mean length46.032872
Min length13

Characters and Unicode

Total characters26607
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)10.9%

Sample

1st row*39 Store all equipment & utensil covered or inverted
2nd row*39 Equipment in good repair and proper adjustment.
3rd row*18 Toxic items storage adjacent to food/utensils
4th row*45 Premises shall be maintained in good repair
5th row*37 Storing the food at least 15 cm (6 inches) above the floor
ValueCountFrequency (%)
food 175
 
4.2%
in 88
 
2.1%
78
 
1.9%
of 74
 
1.8%
good 67
 
1.6%
45 65
 
1.6%
be 65
 
1.6%
repair 63
 
1.5%
47 63
 
1.5%
or 61
 
1.5%
Other values (484) 3331
80.7%
2025-04-14T23:24:20.767193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3626
13.6%
e 2214
 
8.3%
o 1963
 
7.4%
i 1800
 
6.8%
n 1657
 
6.2%
t 1550
 
5.8%
s 1393
 
5.2%
a 1350
 
5.1%
r 1271
 
4.8%
d 964
 
3.6%
Other values (65) 8819
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26607
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3626
13.6%
e 2214
 
8.3%
o 1963
 
7.4%
i 1800
 
6.8%
n 1657
 
6.2%
t 1550
 
5.8%
s 1393
 
5.2%
a 1350
 
5.1%
r 1271
 
4.8%
d 964
 
3.6%
Other values (65) 8819
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26607
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3626
13.6%
e 2214
 
8.3%
o 1963
 
7.4%
i 1800
 
6.8%
n 1657
 
6.2%
t 1550
 
5.8%
s 1393
 
5.2%
a 1350
 
5.1%
r 1271
 
4.8%
d 964
 
3.6%
Other values (65) 8819
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26607
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3626
13.6%
e 2214
 
8.3%
o 1963
 
7.4%
i 1800
 
6.8%
n 1657
 
6.2%
t 1550
 
5.8%
s 1393
 
5.2%
a 1350
 
5.1%
r 1271
 
4.8%
d 964
 
3.6%
Other values (65) 8819
33.1%

Violation Points - 12
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.5%
Missing10098
Missing (%)94.6%
Memory size665.1 KiB
1.0
401 
2.0
111 
3.0
66 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1734
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row3.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 401
 
3.8%
2.0 111
 
1.0%
3.0 66
 
0.6%
(Missing) 10098
94.6%

Length

2025-04-14T23:24:20.932288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:21.037487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 401
69.4%
2.0 111
 
19.2%
3.0 66
 
11.4%

Most occurring characters

ValueCountFrequency (%)
. 578
33.3%
0 578
33.3%
1 401
23.1%
2 111
 
6.4%
3 66
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1734
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 578
33.3%
0 578
33.3%
1 401
23.1%
2 111
 
6.4%
3 66
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1734
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 578
33.3%
0 578
33.3%
1 401
23.1%
2 111
 
6.4%
3 66
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1734
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 578
33.3%
0 578
33.3%
1 401
23.1%
2 111
 
6.4%
3 66
 
3.8%

Violation Detail - 12
Text

Missing 

Distinct142
Distinct (%)25.5%
Missing10119
Missing (%)94.8%
Memory size557.4 KiB
2025-04-14T23:24:21.500697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length888
Median length492
Mean length336.24955
Min length125

Characters and Unicode

Total characters187291
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)11.7%

Sample

1st row228.124 Equipment, Utensils, and Linens. Storage. (a) Equipment, utensils, linens, and single-service and single-use articles. (2) Clean equipment and utensils shall be stored as specified under paragraph (1) of this subsection and shall be stored: (B) covered or inverted.
2nd row228.111 Equipment, Utensils, and Linens. Equipment, maintenance and operation. (a) Good repair and proper adjustment. (1) Equipment shall be maintained in a state of repair and condition that meets the requirements specified in õõ228.101 - 228.106 of this title.
3rd row228.203 Poisonous or Toxic Materials. Storage, separation. Poisonous or toxic materials shall be stored so they cannot contaminate food, equipment, utensils, linens, and single-service and single-use articles by: (1) separating the poisonous or toxic materials by spacing or partitioning; and
4th row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (a) Repairing. The physical facilities shall be maintained in good repair.
5th row228.69 Food. Preventing contamination from the premises. (a) Food Storage. (1) Except as specified in paragraphs (2) and (3) of this subsection, food shall be protected from contamination by storing the food: (C) at least 15 centimeters (6 inches) above the floor.
ValueCountFrequency (%)
and 1362
 
5.3%
food 1034
 
4.1%
of 933
 
3.7%
the 856
 
3.4%
a 700
 
2.7%
shall 605
 
2.4%
in 547
 
2.1%
be 543
 
2.1%
equipment 519
 
2.0%
or 426
 
1.7%
Other values (1129) 17941
70.5%
2025-04-14T23:24:22.049356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38423
20.5%
e 15811
 
8.4%
i 11331
 
6.0%
n 10821
 
5.8%
a 10794
 
5.8%
t 10592
 
5.7%
s 10236
 
5.5%
o 10194
 
5.4%
r 7484
 
4.0%
d 6081
 
3.2%
Other values (60) 55524
29.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 187291
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
38423
20.5%
e 15811
 
8.4%
i 11331
 
6.0%
n 10821
 
5.8%
a 10794
 
5.8%
t 10592
 
5.7%
s 10236
 
5.5%
o 10194
 
5.4%
r 7484
 
4.0%
d 6081
 
3.2%
Other values (60) 55524
29.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 187291
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
38423
20.5%
e 15811
 
8.4%
i 11331
 
6.0%
n 10821
 
5.8%
a 10794
 
5.8%
t 10592
 
5.7%
s 10236
 
5.5%
o 10194
 
5.4%
r 7484
 
4.0%
d 6081
 
3.2%
Other values (60) 55524
29.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 187291
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
38423
20.5%
e 15811
 
8.4%
i 11331
 
6.0%
n 10821
 
5.8%
a 10794
 
5.8%
t 10592
 
5.7%
s 10236
 
5.5%
o 10194
 
5.4%
r 7484
 
4.0%
d 6081
 
3.2%
Other values (60) 55524
29.6%

Violation Memo - 12
Text

Missing 

Distinct474
Distinct (%)89.6%
Missing10147
Missing (%)95.0%
Memory size371.6 KiB
2025-04-14T23:24:22.374473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length502
Median length114
Mean length48.277883
Min length4

Characters and Unicode

Total characters25539
Distinct characters76
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique442 ?
Unique (%)83.6%

Sample

1st rowinvert plates
2nd rowrepair broken lids on prep coolers and cooler gaskets
3rd rowbleach container stored next to clean utensils
4th rowrepair damaged floor tiles, cove base, walls damaged
5th rowobserved food sit on floor-store food 6 inches off the floor
ValueCountFrequency (%)
in 151
 
3.6%
food 116
 
2.8%
clean 100
 
2.4%
on 84
 
2.0%
provide 80
 
1.9%
and 66
 
1.6%
observed 65
 
1.5%
repair 62
 
1.5%
of 61
 
1.5%
the 50
 
1.2%
Other values (838) 3369
80.1%
2025-04-14T23:24:22.865898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3755
 
14.7%
e 2175
 
8.5%
o 1619
 
6.3%
r 1348
 
5.3%
a 1269
 
5.0%
n 1213
 
4.7%
s 1192
 
4.7%
i 1128
 
4.4%
t 1087
 
4.3%
l 899
 
3.5%
Other values (66) 9854
38.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25539
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3755
 
14.7%
e 2175
 
8.5%
o 1619
 
6.3%
r 1348
 
5.3%
a 1269
 
5.0%
n 1213
 
4.7%
s 1192
 
4.7%
i 1128
 
4.4%
t 1087
 
4.3%
l 899
 
3.5%
Other values (66) 9854
38.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25539
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3755
 
14.7%
e 2175
 
8.5%
o 1619
 
6.3%
r 1348
 
5.3%
a 1269
 
5.0%
n 1213
 
4.7%
s 1192
 
4.7%
i 1128
 
4.4%
t 1087
 
4.3%
l 899
 
3.5%
Other values (66) 9854
38.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25539
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3755
 
14.7%
e 2175
 
8.5%
o 1619
 
6.3%
r 1348
 
5.3%
a 1269
 
5.0%
n 1213
 
4.7%
s 1192
 
4.7%
i 1128
 
4.4%
t 1087
 
4.3%
l 899
 
3.5%
Other values (66) 9854
38.6%
Distinct106
Distinct (%)30.5%
Missing10329
Missing (%)96.7%
Memory size357.5 KiB
2025-04-14T23:24:23.119207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length66
Mean length44.634006
Min length16

Characters and Unicode

Total characters15488
Distinct characters76
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)14.1%

Sample

1st row*42 Dirty nonfood contact surfaces
2nd row*47 Conditions of Permit-in use of food equipment
3rd row*47 Health permit posted
4th row*41 Food storage containers, identified with common name of food.
5th row*27 Cooling method, criteria - placing the food in shallow pans
ValueCountFrequency (%)
food 113
 
4.7%
in 54
 
2.2%
52
 
2.1%
of 37
 
1.5%
47 36
 
1.5%
equipment 34
 
1.4%
light 33
 
1.4%
the 33
 
1.4%
or 32
 
1.3%
42 32
 
1.3%
Other values (379) 1963
81.1%
2025-04-14T23:24:23.520183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2113
13.6%
e 1245
 
8.0%
o 1163
 
7.5%
i 1012
 
6.5%
n 908
 
5.9%
t 899
 
5.8%
s 815
 
5.3%
a 774
 
5.0%
r 734
 
4.7%
d 594
 
3.8%
Other values (66) 5231
33.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15488
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2113
13.6%
e 1245
 
8.0%
o 1163
 
7.5%
i 1012
 
6.5%
n 908
 
5.9%
t 899
 
5.8%
s 815
 
5.3%
a 774
 
5.0%
r 734
 
4.7%
d 594
 
3.8%
Other values (66) 5231
33.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15488
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2113
13.6%
e 1245
 
8.0%
o 1163
 
7.5%
i 1012
 
6.5%
n 908
 
5.9%
t 899
 
5.8%
s 815
 
5.3%
a 774
 
5.0%
r 734
 
4.7%
d 594
 
3.8%
Other values (66) 5231
33.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15488
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2113
13.6%
e 1245
 
8.0%
o 1163
 
7.5%
i 1012
 
6.5%
n 908
 
5.9%
t 899
 
5.8%
s 815
 
5.3%
a 774
 
5.0%
r 734
 
4.7%
d 594
 
3.8%
Other values (66) 5231
33.8%

Violation Points - 13
Categorical

High correlation  Missing 

Distinct3
Distinct (%)0.9%
Missing10329
Missing (%)96.7%
Memory size666.0 KiB
1.0
238 
2.0
74 
3.0
35 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1041
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row2.0

Common Values

ValueCountFrequency (%)
1.0 238
 
2.2%
2.0 74
 
0.7%
3.0 35
 
0.3%
(Missing) 10329
96.7%

Length

2025-04-14T23:24:23.639508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:23.708848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 238
68.6%
2.0 74
 
21.3%
3.0 35
 
10.1%

Most occurring characters

ValueCountFrequency (%)
. 347
33.3%
0 347
33.3%
1 238
22.9%
2 74
 
7.1%
3 35
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1041
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 347
33.3%
0 347
33.3%
1 238
22.9%
2 74
 
7.1%
3 35
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1041
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 347
33.3%
0 347
33.3%
1 238
22.9%
2 74
 
7.1%
3 35
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1041
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 347
33.3%
0 347
33.3%
1 238
22.9%
2 74
 
7.1%
3 35
 
3.4%

Violation Detail - 13
Text

Missing 

Distinct105
Distinct (%)31.7%
Missing10345
Missing (%)96.9%
Memory size464.5 KiB
2025-04-14T23:24:23.968557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length815
Median length455
Mean length338.37764
Min length184

Characters and Unicode

Total characters112003
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)14.8%

Sample

1st row228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.
2nd row228.248 Compliance Conditions of retention, responsibilities of the permit holder. Upon acceptance of the permit issued by the regulatory authority, the permit holder in order to retain the permit shall: (11) Notify customers that a copy of the most recent establishment inspection report is available upon request by posting a sign or placard in a location in the food establishment that is conspicuous to customers or by another method acceptable to the regulatory authority.
3rd rowSEC. 17-10.2. ADDITIONAL REQUIREMENTS. (c) Permits. (11) Display. A food establishment that operates from a fixed facility shall display its permit in a frame with a glass cover at a prominent place inside the facility where it can be easily seen by the public.
4th row228.66 Food. Preventing food and ingredient contamination. (b) Food storage containers, identified with common name of food. Except for containers holding food that can be readily and unmistakably recognized such as dry pasta, working containers holding food or food ingredients that are removed from their original packages for use in the food establishment, such as cooking oils, flour, herbs, potato flakes, salt, spices, and sugar shall be identified with the common name of the food.
5th row228.75 Food. Time and temperature control. (e) Cooling methods. (1) Cooling shall be accomplished in accordance with the time and temperature criteria specified in subsection (d) of this section by using one or more of the following methods based on the type of food being cooled: (A) placing the food in shallow pans;
ValueCountFrequency (%)
and 840
 
5.5%
food 637
 
4.2%
of 513
 
3.4%
the 467
 
3.1%
a 410
 
2.7%
shall 358
 
2.4%
be 322
 
2.1%
in 320
 
2.1%
equipment 299
 
2.0%
or 242
 
1.6%
Other values (986) 10805
71.0%
2025-04-14T23:24:24.416882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23029
20.6%
e 9403
 
8.4%
i 6719
 
6.0%
a 6510
 
5.8%
n 6378
 
5.7%
t 6220
 
5.6%
s 6163
 
5.5%
o 5992
 
5.3%
r 4452
 
4.0%
d 3766
 
3.4%
Other values (61) 33371
29.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 112003
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
23029
20.6%
e 9403
 
8.4%
i 6719
 
6.0%
a 6510
 
5.8%
n 6378
 
5.7%
t 6220
 
5.6%
s 6163
 
5.5%
o 5992
 
5.3%
r 4452
 
4.0%
d 3766
 
3.4%
Other values (61) 33371
29.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 112003
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
23029
20.6%
e 9403
 
8.4%
i 6719
 
6.0%
a 6510
 
5.8%
n 6378
 
5.7%
t 6220
 
5.6%
s 6163
 
5.5%
o 5992
 
5.3%
r 4452
 
4.0%
d 3766
 
3.4%
Other values (61) 33371
29.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 112003
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
23029
20.6%
e 9403
 
8.4%
i 6719
 
6.0%
a 6510
 
5.8%
n 6378
 
5.7%
t 6220
 
5.6%
s 6163
 
5.5%
o 5992
 
5.3%
r 4452
 
4.0%
d 3766
 
3.4%
Other values (61) 33371
29.8%

Violation Memo - 13
Text

Missing 

Distinct310
Distinct (%)95.1%
Missing10350
Missing (%)96.9%
Memory size357.7 KiB
2025-04-14T23:24:24.775355image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length213
Median length100
Mean length49.616564
Min length4

Characters and Unicode

Total characters16175
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique297 ?
Unique (%)91.1%

Sample

1st rowClean vent hood, fryer station, all shelves, cooler gaskets, WIC shelves, portable burners, soda syrup spills under soda fountain, utensil dispenser
2nd rowsign about inspection report
3rd rowhealth permit not posted
4th rowprovide label for food storage containers
5th rowcooling hot food in a closed bag must use shallow container
ValueCountFrequency (%)
in 72
 
2.7%
food 69
 
2.6%
clean 67
 
2.5%
provide 54
 
2.0%
on 51
 
1.9%
and 43
 
1.6%
repair 37
 
1.4%
observed 36
 
1.4%
at 34
 
1.3%
all 33
 
1.2%
Other values (686) 2169
81.4%
2025-04-14T23:24:25.275252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2364
 
14.6%
e 1378
 
8.5%
o 1055
 
6.5%
a 887
 
5.5%
n 843
 
5.2%
r 828
 
5.1%
s 784
 
4.8%
t 753
 
4.7%
i 741
 
4.6%
l 589
 
3.6%
Other values (65) 5953
36.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16175
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2364
 
14.6%
e 1378
 
8.5%
o 1055
 
6.5%
a 887
 
5.5%
n 843
 
5.2%
r 828
 
5.1%
s 784
 
4.8%
t 753
 
4.7%
i 741
 
4.6%
l 589
 
3.6%
Other values (65) 5953
36.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16175
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2364
 
14.6%
e 1378
 
8.5%
o 1055
 
6.5%
a 887
 
5.5%
n 843
 
5.2%
r 828
 
5.1%
s 784
 
4.8%
t 753
 
4.7%
i 741
 
4.6%
l 589
 
3.6%
Other values (65) 5953
36.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16175
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2364
 
14.6%
e 1378
 
8.5%
o 1055
 
6.5%
a 887
 
5.5%
n 843
 
5.2%
r 828
 
5.1%
s 784
 
4.8%
t 753
 
4.7%
i 741
 
4.6%
l 589
 
3.6%
Other values (65) 5953
36.8%
Distinct91
Distinct (%)43.5%
Missing10467
Missing (%)98.0%
Memory size348.7 KiB
2025-04-14T23:24:25.560014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length65
Mean length47.095694
Min length20

Characters and Unicode

Total characters9843
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)23.0%

Sample

1st row*47 Other Violations
2nd row*43 Light bulbs, light shields provided
3rd row*45 Premises shall be maintained in good repair
4th row*32 Damaged Equipment
5th row*45 Premises shall be maintained in good repair
ValueCountFrequency (%)
food 60
 
3.9%
39
 
2.5%
in 35
 
2.3%
for 24
 
1.6%
be 23
 
1.5%
45 23
 
1.5%
repair 22
 
1.4%
of 22
 
1.4%
good 22
 
1.4%
equipment 21
 
1.4%
Other values (359) 1239
81.0%
2025-04-14T23:24:26.006097image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1350
13.7%
e 825
 
8.4%
o 728
 
7.4%
n 630
 
6.4%
i 626
 
6.4%
t 581
 
5.9%
s 556
 
5.6%
a 523
 
5.3%
r 473
 
4.8%
d 341
 
3.5%
Other values (62) 3210
32.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9843
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1350
13.7%
e 825
 
8.4%
o 728
 
7.4%
n 630
 
6.4%
i 626
 
6.4%
t 581
 
5.9%
s 556
 
5.6%
a 523
 
5.3%
r 473
 
4.8%
d 341
 
3.5%
Other values (62) 3210
32.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9843
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1350
13.7%
e 825
 
8.4%
o 728
 
7.4%
n 630
 
6.4%
i 626
 
6.4%
t 581
 
5.9%
s 556
 
5.6%
a 523
 
5.3%
r 473
 
4.8%
d 341
 
3.5%
Other values (62) 3210
32.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9843
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1350
13.7%
e 825
 
8.4%
o 728
 
7.4%
n 630
 
6.4%
i 626
 
6.4%
t 581
 
5.9%
s 556
 
5.6%
a 523
 
5.3%
r 473
 
4.8%
d 341
 
3.5%
Other values (62) 3210
32.6%

Violation Points - 14
Categorical

Missing 

Distinct3
Distinct (%)1.4%
Missing10467
Missing (%)98.0%
Memory size666.6 KiB
1.0
136 
2.0
48 
3.0
25 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters627
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row2.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 136
 
1.3%
2.0 48
 
0.4%
3.0 25
 
0.2%
(Missing) 10467
98.0%

Length

2025-04-14T23:24:26.114511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:26.185054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 136
65.1%
2.0 48
 
23.0%
3.0 25
 
12.0%

Most occurring characters

ValueCountFrequency (%)
. 209
33.3%
0 209
33.3%
1 136
21.7%
2 48
 
7.7%
3 25
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 627
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 209
33.3%
0 209
33.3%
1 136
21.7%
2 48
 
7.7%
3 25
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 627
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 209
33.3%
0 209
33.3%
1 136
21.7%
2 48
 
7.7%
3 25
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 627
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 209
33.3%
0 209
33.3%
1 136
21.7%
2 48
 
7.7%
3 25
 
4.0%

Violation Detail - 14
Text

Missing 

Distinct90
Distinct (%)44.1%
Missing10472
Missing (%)98.1%
Memory size419.6 KiB
2025-04-14T23:24:26.481889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length829
Median length454
Mean length345.93137
Min length148

Characters and Unicode

Total characters70570
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)23.5%

Sample

1st row228.174 Physical Facilities. Functionality. (a) Light bulbs, protective shielding. (1) Except as specified in paragraph (2) of this subsection, light bulbs shall be shielded, coated, or otherwise shatter-resistant in areas where there is exposed food; clean equipment, utensils, and linens; or unwrapped single-service and single-use articles.
2nd row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (a) Repairing. The physical facilities shall be maintained in good repair.
3rd row228.104 Equipment, Utensils, and Linens. Cleanability. (a) Food-contact surfaces. Multi use food-contact surfaces shall be: (2) free of breaks, open seams, cracks, chips, inclusions, pits, and similar imperfections;
4th row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (a) Repairing. The physical facilities shall be maintained in good repair.
5th row228.106 Equipment, Utensils, and Linens. Functionality of equipment. (a) Ventilation hood systems, drip prevention. Exhaust ventilation hood systems in food preparation and warewashing areas including components such as hoods, fans, guards, and ducting shall be designed to prevent grease or condensation from draining or dripping onto food, equipment, utensils, linens, and single-service and single-use articles.
ValueCountFrequency (%)
and 564
 
5.9%
food 373
 
3.9%
of 320
 
3.3%
the 289
 
3.0%
a 274
 
2.9%
shall 216
 
2.3%
be 203
 
2.1%
in 201
 
2.1%
equipment 199
 
2.1%
or 154
 
1.6%
Other values (893) 6777
70.8%
2025-04-14T23:24:26.975988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14451
20.5%
e 5988
 
8.5%
i 4338
 
6.1%
n 4155
 
5.9%
a 4130
 
5.9%
t 3989
 
5.7%
s 3874
 
5.5%
o 3726
 
5.3%
r 2748
 
3.9%
d 2327
 
3.3%
Other values (61) 20844
29.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 70570
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
14451
20.5%
e 5988
 
8.5%
i 4338
 
6.1%
n 4155
 
5.9%
a 4130
 
5.9%
t 3989
 
5.7%
s 3874
 
5.5%
o 3726
 
5.3%
r 2748
 
3.9%
d 2327
 
3.3%
Other values (61) 20844
29.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 70570
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
14451
20.5%
e 5988
 
8.5%
i 4338
 
6.1%
n 4155
 
5.9%
a 4130
 
5.9%
t 3989
 
5.7%
s 3874
 
5.5%
o 3726
 
5.3%
r 2748
 
3.9%
d 2327
 
3.3%
Other values (61) 20844
29.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 70570
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
14451
20.5%
e 5988
 
8.5%
i 4338
 
6.1%
n 4155
 
5.9%
a 4130
 
5.9%
t 3989
 
5.7%
s 3874
 
5.5%
o 3726
 
5.3%
r 2748
 
3.9%
d 2327
 
3.3%
Other values (61) 20844
29.5%

Violation Memo - 14
Text

Missing 

Distinct189
Distinct (%)96.4%
Missing10480
Missing (%)98.2%
Memory size347.8 KiB
2025-04-14T23:24:27.300159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length172
Median length68
Mean length48.158163
Min length5

Characters and Unicode

Total characters9439
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique183 ?
Unique (%)93.4%

Sample

1st rowProvide choking poster in dining room
2nd rowreplace light bulbs on vent a hood
3rd rowrepair damaged cove base, ceiling tiles, wall tiles
4th rowDishwasher leaking, repair peeling in ice machine
5th rowRepair damaged tile floor in kitchen area
ValueCountFrequency (%)
in 51
 
3.3%
food 39
 
2.5%
on 30
 
1.9%
clean 26
 
1.7%
provide 25
 
1.6%
and 24
 
1.5%
the 21
 
1.3%
repair 20
 
1.3%
floor 19
 
1.2%
for 19
 
1.2%
Other values (494) 1295
82.5%
2025-04-14T23:24:27.800960image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1385
 
14.7%
e 779
 
8.3%
o 581
 
6.2%
n 509
 
5.4%
a 491
 
5.2%
r 480
 
5.1%
i 478
 
5.1%
t 459
 
4.9%
s 447
 
4.7%
d 312
 
3.3%
Other values (62) 3518
37.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9439
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1385
 
14.7%
e 779
 
8.3%
o 581
 
6.2%
n 509
 
5.4%
a 491
 
5.2%
r 480
 
5.1%
i 478
 
5.1%
t 459
 
4.9%
s 447
 
4.7%
d 312
 
3.3%
Other values (62) 3518
37.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9439
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1385
 
14.7%
e 779
 
8.3%
o 581
 
6.2%
n 509
 
5.4%
a 491
 
5.2%
r 480
 
5.1%
i 478
 
5.1%
t 459
 
4.9%
s 447
 
4.7%
d 312
 
3.3%
Other values (62) 3518
37.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9439
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1385
 
14.7%
e 779
 
8.3%
o 581
 
6.2%
n 509
 
5.4%
a 491
 
5.2%
r 480
 
5.1%
i 478
 
5.1%
t 459
 
4.9%
s 447
 
4.7%
d 312
 
3.3%
Other values (62) 3518
37.3%
Distinct62
Distinct (%)43.1%
Missing10532
Missing (%)98.7%
Memory size343.5 KiB
2025-04-14T23:24:28.041365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length99
Median length63.5
Mean length42.381944
Min length16

Characters and Unicode

Total characters6103
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)23.6%

Sample

1st row*35 Eating food, chewing gum, drinking beverages, or using tobacco
2nd row*46 Covered waste receptacle for women's restroom
3rd row*22 Accredited food handler certificate - 60 days
4th row*14 Hands wash procedures-without soap
5th row*47 Permit/license posted
ValueCountFrequency (%)
food 46
 
4.8%
47 23
 
2.4%
21
 
2.2%
of 19
 
2.0%
in 19
 
2.0%
or 14
 
1.5%
good 13
 
1.4%
45 12
 
1.3%
equipment 12
 
1.3%
repair 11
 
1.1%
Other values (260) 769
80.2%
2025-04-14T23:24:28.415491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
829
 
13.6%
e 499
 
8.2%
o 448
 
7.3%
i 378
 
6.2%
n 351
 
5.8%
t 335
 
5.5%
a 326
 
5.3%
s 311
 
5.1%
r 294
 
4.8%
d 246
 
4.0%
Other values (60) 2086
34.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6103
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
829
 
13.6%
e 499
 
8.2%
o 448
 
7.3%
i 378
 
6.2%
n 351
 
5.8%
t 335
 
5.5%
a 326
 
5.3%
s 311
 
5.1%
r 294
 
4.8%
d 246
 
4.0%
Other values (60) 2086
34.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6103
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
829
 
13.6%
e 499
 
8.2%
o 448
 
7.3%
i 378
 
6.2%
n 351
 
5.8%
t 335
 
5.5%
a 326
 
5.3%
s 311
 
5.1%
r 294
 
4.8%
d 246
 
4.0%
Other values (60) 2086
34.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6103
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
829
 
13.6%
e 499
 
8.2%
o 448
 
7.3%
i 378
 
6.2%
n 351
 
5.8%
t 335
 
5.5%
a 326
 
5.3%
s 311
 
5.1%
r 294
 
4.8%
d 246
 
4.0%
Other values (60) 2086
34.2%

Violation Points - 15
Categorical

High correlation  Missing 

Distinct3
Distinct (%)2.1%
Missing10532
Missing (%)98.7%
Memory size666.8 KiB
1.0
90 
3.0
28 
2.0
26 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters432
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row2.0
4th row3.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 90
 
0.8%
3.0 28
 
0.3%
2.0 26
 
0.2%
(Missing) 10532
98.7%

Length

2025-04-14T23:24:28.527316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:28.598805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 90
62.5%
3.0 28
 
19.4%
2.0 26
 
18.1%

Most occurring characters

ValueCountFrequency (%)
. 144
33.3%
0 144
33.3%
1 90
20.8%
3 28
 
6.5%
2 26
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 432
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 144
33.3%
0 144
33.3%
1 90
20.8%
3 28
 
6.5%
2 26
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 432
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 144
33.3%
0 144
33.3%
1 90
20.8%
3 28
 
6.5%
2 26
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 432
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 144
33.3%
0 144
33.3%
1 90
20.8%
3 28
 
6.5%
2 26
 
6.0%

Violation Detail - 15
Text

Missing 

Distinct61
Distinct (%)43.6%
Missing10536
Missing (%)98.7%
Memory size392.1 KiB
2025-04-14T23:24:28.876485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length829
Median length469.5
Mean length350.75
Min length184

Characters and Unicode

Total characters49105
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)24.3%

Sample

1st row228.42 Management and Personnel. Food Contamination Prevention (a) Eating, drinking, or using tobacco. (1) except as specified in paragraph (2) of this subsection, an employee shall eat, drink, or use any form of tobacco only in designated areas where the contamination of exposed food; clean equipment, utensils, and linens; unwrapped single-service and single-use articles; or other items needing protection cannot result.
2nd row228.152 Water, Plumbing, and Waste. Refuse, Recyclables, and Returnables, Facilities on the Premises. (h) Toilet room receptacle, covered. A toilet room used by females shall be provided with a covered receptacle for sanitary napkins.
3rd rowõ228.33. Certified Food Protection Manager and Food Handler Requirements (d) Except in a temporary food establishment and the certified food manager, all food employees shall successfully complete an accredited food handler training course, within 60 days of employment.
4th row228.38 Management and Personnel. Hands and arms (b) Cleaning Procedure. (1) Except as specified in subsection (d) of this section, food employees shall clean their hands and exposed portions of their arms (or surrogate prosthetic devices for hands or arms) for at least 20 seconds, using a cleaning compound in a handwashing sink that is equipped as specified under õ228.146 and õ228.175 of this title (relating to Water, Plumbing, and Waste).
5th row228.248 COMPLIANCE Conditions of Retention, Responsibilities of the Permit Holder Upon acceptance of the permit issued by the regulatory authority, the permit holder in order to retain the permit shall: (1) post the permit in a location in the food establishment that is conspicuous to consumers;
ValueCountFrequency (%)
and 348
 
5.1%
food 289
 
4.2%
the 246
 
3.6%
of 221
 
3.2%
a 200
 
2.9%
shall 159
 
2.3%
in 140
 
2.0%
be 133
 
1.9%
or 109
 
1.6%
equipment 93
 
1.4%
Other values (759) 4895
71.6%
2025-04-14T23:24:29.328159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9870
20.1%
e 4173
 
8.5%
i 2901
 
5.9%
a 2897
 
5.9%
n 2739
 
5.6%
t 2729
 
5.6%
o 2704
 
5.5%
s 2686
 
5.5%
r 2004
 
4.1%
d 1667
 
3.4%
Other values (60) 14735
30.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49105
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9870
20.1%
e 4173
 
8.5%
i 2901
 
5.9%
a 2897
 
5.9%
n 2739
 
5.6%
t 2729
 
5.6%
o 2704
 
5.5%
s 2686
 
5.5%
r 2004
 
4.1%
d 1667
 
3.4%
Other values (60) 14735
30.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49105
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9870
20.1%
e 4173
 
8.5%
i 2901
 
5.9%
a 2897
 
5.9%
n 2739
 
5.6%
t 2729
 
5.6%
o 2704
 
5.5%
s 2686
 
5.5%
r 2004
 
4.1%
d 1667
 
3.4%
Other values (60) 14735
30.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49105
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9870
20.1%
e 4173
 
8.5%
i 2901
 
5.9%
a 2897
 
5.9%
n 2739
 
5.6%
t 2729
 
5.6%
o 2704
 
5.5%
s 2686
 
5.5%
r 2004
 
4.1%
d 1667
 
3.4%
Other values (60) 14735
30.0%

Violation Memo - 15
Text

Missing 

Distinct127
Distinct (%)96.9%
Missing10545
Missing (%)98.8%
Memory size343.6 KiB
2025-04-14T23:24:29.623875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length436
Median length86
Mean length52.328244
Min length4

Characters and Unicode

Total characters6855
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)94.7%

Sample

1st rowobserved employee drinks from cup during food preparation
2nd rowprovide covered receptacle in restroom
3rd rowPost Health Permit, tax permit, consumer health sign
4th rowClean dusty ceilings, WIC floor, WIC shelves, vent hoods, and walls.
5th rowNo mop sink seen.
ValueCountFrequency (%)
in 36
 
3.2%
food 28
 
2.5%
clean 27
 
2.4%
on 24
 
2.1%
observed 23
 
2.0%
provide 21
 
1.9%
of 20
 
1.8%
sink 18
 
1.6%
hand 18
 
1.6%
no 16
 
1.4%
Other values (418) 901
79.6%
2025-04-14T23:24:30.069473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1031
 
15.0%
e 493
 
7.2%
o 363
 
5.3%
n 295
 
4.3%
r 285
 
4.2%
a 283
 
4.1%
i 277
 
4.0%
s 272
 
4.0%
t 254
 
3.7%
d 208
 
3.0%
Other values (59) 3094
45.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6855
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1031
 
15.0%
e 493
 
7.2%
o 363
 
5.3%
n 295
 
4.3%
r 285
 
4.2%
a 283
 
4.1%
i 277
 
4.0%
s 272
 
4.0%
t 254
 
3.7%
d 208
 
3.0%
Other values (59) 3094
45.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6855
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1031
 
15.0%
e 493
 
7.2%
o 363
 
5.3%
n 295
 
4.3%
r 285
 
4.2%
a 283
 
4.1%
i 277
 
4.0%
s 272
 
4.0%
t 254
 
3.7%
d 208
 
3.0%
Other values (59) 3094
45.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6855
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1031
 
15.0%
e 493
 
7.2%
o 363
 
5.3%
n 295
 
4.3%
r 285
 
4.2%
a 283
 
4.1%
i 277
 
4.0%
s 272
 
4.0%
t 254
 
3.7%
d 208
 
3.0%
Other values (59) 3094
45.1%
Distinct51
Distinct (%)60.7%
Missing10592
Missing (%)99.2%
Memory size339.6 KiB
2025-04-14T23:24:30.298492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length59
Mean length45.285714
Min length16

Characters and Unicode

Total characters3804
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)41.7%

Sample

1st row*42 Dirty nonfood contact surfaces
2nd row*34 Pest control-routine inspections for
3rd row*31 Handwashing lavatory - used for other purpose
4th row*42 Dirty nonfood contact surfaces
5th row*02 Cold Hold (41øF/45øF or below)
ValueCountFrequency (%)
food 24
 
4.1%
20
 
3.4%
in 10
 
1.7%
light 10
 
1.7%
shall 10
 
1.7%
good 8
 
1.4%
be 8
 
1.4%
43 8
 
1.4%
45 7
 
1.2%
clean 7
 
1.2%
Other values (223) 468
80.7%
2025-04-14T23:24:30.660966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
509
 
13.4%
e 301
 
7.9%
o 270
 
7.1%
i 255
 
6.7%
n 231
 
6.1%
t 231
 
6.1%
s 200
 
5.3%
a 189
 
5.0%
r 183
 
4.8%
d 144
 
3.8%
Other values (59) 1291
33.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3804
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
509
 
13.4%
e 301
 
7.9%
o 270
 
7.1%
i 255
 
6.7%
n 231
 
6.1%
t 231
 
6.1%
s 200
 
5.3%
a 189
 
5.0%
r 183
 
4.8%
d 144
 
3.8%
Other values (59) 1291
33.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3804
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
509
 
13.4%
e 301
 
7.9%
o 270
 
7.1%
i 255
 
6.7%
n 231
 
6.1%
t 231
 
6.1%
s 200
 
5.3%
a 189
 
5.0%
r 183
 
4.8%
d 144
 
3.8%
Other values (59) 1291
33.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3804
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
509
 
13.4%
e 301
 
7.9%
o 270
 
7.1%
i 255
 
6.7%
n 231
 
6.1%
t 231
 
6.1%
s 200
 
5.3%
a 189
 
5.0%
r 183
 
4.8%
d 144
 
3.8%
Other values (59) 1291
33.9%

Violation Points - 16
Categorical

High correlation  Missing 

Distinct3
Distinct (%)3.6%
Missing10592
Missing (%)99.2%
Memory size667.1 KiB
1.0
56 
2.0
15 
3.0
13 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters252
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row2.0
4th row1.0
5th row3.0

Common Values

ValueCountFrequency (%)
1.0 56
 
0.5%
2.0 15
 
0.1%
3.0 13
 
0.1%
(Missing) 10592
99.2%

Length

2025-04-14T23:24:30.780079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:30.843516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 56
66.7%
2.0 15
 
17.9%
3.0 13
 
15.5%

Most occurring characters

ValueCountFrequency (%)
. 84
33.3%
0 84
33.3%
1 56
22.2%
2 15
 
6.0%
3 13
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 252
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 84
33.3%
0 84
33.3%
1 56
22.2%
2 15
 
6.0%
3 13
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 252
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 84
33.3%
0 84
33.3%
1 56
22.2%
2 15
 
6.0%
3 13
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 252
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 84
33.3%
0 84
33.3%
1 56
22.2%
2 15
 
6.0%
3 13
 
5.2%

Violation Detail - 16
Text

Missing 

Distinct49
Distinct (%)62.8%
Missing10598
Missing (%)99.3%
Memory size364.5 KiB
2025-04-14T23:24:31.113903image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length714
Median length419
Mean length319.70513
Min length163

Characters and Unicode

Total characters24937
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)44.9%

Sample

1st row228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.
2nd row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (k) Controlling pests. The presence of insects, rodents, and other pests shall be controlled to minimize their presence within the physical facility and its contents, and on the contiguous land or property under the control of the permit holder by: (2) routinely inspecting the premises for evidence of pests;
3rd row228.149 Water, Plumbing, and Waste. Plumbing, operation and maintenance. (a) Using a handwashing facility. (2) A handwashing facility may not be used for purposes other than handwashing.
4th row228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.
5th row228.75 Food. Time and temperature control. (f) Time/temperature controlled for safety food, hot and cold holding. (1) Except during preparation, cooking, or cooling, or when time is used as the public health control as specified in subsection (i) of this section, and except as specified in paragraphs (2) and (3) of this subsection, TCS food shall be maintained: (B) at 5 degrees Celsius (41 degrees Fahrenheit) or less;
ValueCountFrequency (%)
and 210
 
6.3%
food 119
 
3.6%
of 110
 
3.3%
the 90
 
2.7%
shall 84
 
2.5%
a 82
 
2.5%
equipment 78
 
2.3%
be 71
 
2.1%
in 63
 
1.9%
utensils 52
 
1.6%
Other values (599) 2374
71.2%
2025-04-14T23:24:31.566261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5051
20.3%
e 2089
 
8.4%
i 1518
 
6.1%
n 1472
 
5.9%
s 1445
 
5.8%
a 1439
 
5.8%
t 1373
 
5.5%
o 1256
 
5.0%
r 920
 
3.7%
l 841
 
3.4%
Other values (57) 7533
30.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24937
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5051
20.3%
e 2089
 
8.4%
i 1518
 
6.1%
n 1472
 
5.9%
s 1445
 
5.8%
a 1439
 
5.8%
t 1373
 
5.5%
o 1256
 
5.0%
r 920
 
3.7%
l 841
 
3.4%
Other values (57) 7533
30.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24937
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5051
20.3%
e 2089
 
8.4%
i 1518
 
6.1%
n 1472
 
5.9%
s 1445
 
5.8%
a 1439
 
5.8%
t 1373
 
5.5%
o 1256
 
5.0%
r 920
 
3.7%
l 841
 
3.4%
Other values (57) 7533
30.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24937
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5051
20.3%
e 2089
 
8.4%
i 1518
 
6.1%
n 1472
 
5.9%
s 1445
 
5.8%
a 1439
 
5.8%
t 1373
 
5.5%
o 1256
 
5.0%
r 920
 
3.7%
l 841
 
3.4%
Other values (57) 7533
30.2%

Violation Memo - 16
Text

Missing 

Distinct73
Distinct (%)96.1%
Missing10600
Missing (%)99.3%
Memory size339.5 KiB
2025-04-14T23:24:32.053161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length327
Median length68
Mean length53.052632
Min length4

Characters and Unicode

Total characters4032
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)92.1%

Sample

1st rowclean shelves in coolers, clean shelves in the kitchen, clean gaskets, cabinets, ovens
2nd rowObserved multiple flies in kitchen area and provide pest control record on site
3rd rowHand sinks are for hand washing only
4th rowclean shelves, gaskets, freezer,
5th rowImproper cold holding: red salsa 53, green salsa 52.6, ranch 55, sour cream 53.8, RIC 59.5, onions 48.7, pico de gallo 50.3, tomatoes 49.6, pico de gallo 49.6, green salsa 45, red salsa 43, rice 47.3, rice 46.5, bell pepper 46, RIC 48, chicken 46.4, and soup 44.0. Discarded and voluntary destruction form filled out.
ValueCountFrequency (%)
in 18
 
2.8%
sink 15
 
2.3%
clean 14
 
2.2%
provide 14
 
2.2%
food 13
 
2.0%
hand 12
 
1.8%
observed 12
 
1.8%
and 11
 
1.7%
on 11
 
1.7%
repair 9
 
1.4%
Other values (296) 521
80.2%
2025-04-14T23:24:32.788415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
584
 
14.5%
e 338
 
8.4%
o 219
 
5.4%
n 206
 
5.1%
a 205
 
5.1%
r 201
 
5.0%
s 193
 
4.8%
i 193
 
4.8%
t 174
 
4.3%
l 152
 
3.8%
Other values (57) 1567
38.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4032
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
584
 
14.5%
e 338
 
8.4%
o 219
 
5.4%
n 206
 
5.1%
a 205
 
5.1%
r 201
 
5.0%
s 193
 
4.8%
i 193
 
4.8%
t 174
 
4.3%
l 152
 
3.8%
Other values (57) 1567
38.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4032
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
584
 
14.5%
e 338
 
8.4%
o 219
 
5.4%
n 206
 
5.1%
a 205
 
5.1%
r 201
 
5.0%
s 193
 
4.8%
i 193
 
4.8%
t 174
 
4.3%
l 152
 
3.8%
Other values (57) 1567
38.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4032
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
584
 
14.5%
e 338
 
8.4%
o 219
 
5.4%
n 206
 
5.1%
a 205
 
5.1%
r 201
 
5.0%
s 193
 
4.8%
i 193
 
4.8%
t 174
 
4.3%
l 152
 
3.8%
Other values (57) 1567
38.9%
Distinct31
Distinct (%)66.0%
Missing10629
Missing (%)99.6%
Memory size337.0 KiB
2025-04-14T23:24:33.272344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length97
Median length49
Mean length45.191489
Min length20

Characters and Unicode

Total characters2124
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)44.7%

Sample

1st row*41 Food storage containers, identified with common name of food.
2nd row*40 Reuse of single service articles
3rd row*19 Water & Plumbing in good repair- per code
4th row*43 Ventilation hood systems, adequacy
5th row*46 Covered waste receptacle for women's restroom
ValueCountFrequency (%)
food 19
 
5.4%
of 11
 
3.2%
47 8
 
2.3%
the 8
 
2.3%
in 6
 
1.7%
with 6
 
1.7%
repair 6
 
1.7%
6
 
1.7%
good 5
 
1.4%
45 5
 
1.4%
Other values (141) 269
77.1%
2025-04-14T23:24:33.968819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
309
14.5%
e 181
 
8.5%
o 162
 
7.6%
i 132
 
6.2%
t 126
 
5.9%
n 124
 
5.8%
a 115
 
5.4%
s 112
 
5.3%
r 86
 
4.0%
d 83
 
3.9%
Other values (54) 694
32.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2124
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
309
14.5%
e 181
 
8.5%
o 162
 
7.6%
i 132
 
6.2%
t 126
 
5.9%
n 124
 
5.8%
a 115
 
5.4%
s 112
 
5.3%
r 86
 
4.0%
d 83
 
3.9%
Other values (54) 694
32.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2124
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
309
14.5%
e 181
 
8.5%
o 162
 
7.6%
i 132
 
6.2%
t 126
 
5.9%
n 124
 
5.8%
a 115
 
5.4%
s 112
 
5.3%
r 86
 
4.0%
d 83
 
3.9%
Other values (54) 694
32.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2124
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
309
14.5%
e 181
 
8.5%
o 162
 
7.6%
i 132
 
6.2%
t 126
 
5.9%
n 124
 
5.8%
a 115
 
5.4%
s 112
 
5.3%
r 86
 
4.0%
d 83
 
3.9%
Other values (54) 694
32.7%

Violation Points - 17
Categorical

High correlation  Missing 

Distinct3
Distinct (%)6.4%
Missing10629
Missing (%)99.6%
Memory size667.2 KiB
1.0
33 
3.0
2.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters141
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row3.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 33
 
0.3%
3.0 8
 
0.1%
2.0 6
 
0.1%
(Missing) 10629
99.6%

Length

2025-04-14T23:24:34.139676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:34.244131image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 33
70.2%
3.0 8
 
17.0%
2.0 6
 
12.8%

Most occurring characters

ValueCountFrequency (%)
. 47
33.3%
0 47
33.3%
1 33
23.4%
3 8
 
5.7%
2 6
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 141
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 47
33.3%
0 47
33.3%
1 33
23.4%
3 8
 
5.7%
2 6
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 141
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 47
33.3%
0 47
33.3%
1 33
23.4%
3 8
 
5.7%
2 6
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 141
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 47
33.3%
0 47
33.3%
1 33
23.4%
3 8
 
5.7%
2 6
 
4.3%

Violation Detail - 17
Text

Missing 

Distinct30
Distinct (%)66.7%
Missing10631
Missing (%)99.6%
Memory size351.9 KiB
2025-04-14T23:24:34.587270image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length815
Median length375
Mean length353.2
Min length198

Characters and Unicode

Total characters15894
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)46.7%

Sample

1st row228.66 Food. Preventing food and ingredient contamination. (b) Food storage containers, identified with common name of food. Except for containers holding food that can be readily and unmistakably recognized such as dry pasta, working containers holding food or food ingredients that are removed from their original packages for use in the food establishment, such as cooking oils, flour, herbs, potato flakes, salt, spices, and sugar shall be identified with the common name of the food.
2nd row228.112 Equipment, Utensils, and Linens. Utensils and Temperature and Pressure Measuring Devices. (c) Single-service and single-use articles use limitation. (1) Single-service and single-use articles may not be reused.
3rd row228.149 Water, Plumbing, and Waste. Plumbing, operation and maintenance. (e) System maintained in good repair. A plumbing system shall be: (1) repaired according to the Plumbing Code; and
4th row228.107 Equipment, Utensils, and Linens. Equipment, numbers and capacities. (d) Ventilation hood systems, adequacy. Ventilation hood systems and devices shall be sufficient in number and capacity to prevent grease or condensation from collecting on walls and ceilings.
5th row228.152 Water, Plumbing, and Waste. Refuse, Recyclables, and Returnables, Facilities on the Premises. (h) Toilet room receptacle, covered. A toilet room used by females shall be provided with a covered receptacle for sanitary napkins.
ValueCountFrequency (%)
and 122
 
5.6%
food 120
 
5.5%
the 83
 
3.8%
of 61
 
2.8%
a 53
 
2.4%
be 51
 
2.3%
shall 51
 
2.3%
in 49
 
2.2%
or 35
 
1.6%
equipment 31
 
1.4%
Other values (448) 1530
70.0%
2025-04-14T23:24:35.680966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3306
20.8%
e 1349
 
8.5%
i 970
 
6.1%
a 939
 
5.9%
o 912
 
5.7%
n 890
 
5.6%
t 881
 
5.5%
s 880
 
5.5%
r 615
 
3.9%
d 550
 
3.5%
Other values (56) 4602
29.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15894
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3306
20.8%
e 1349
 
8.5%
i 970
 
6.1%
a 939
 
5.9%
o 912
 
5.7%
n 890
 
5.6%
t 881
 
5.5%
s 880
 
5.5%
r 615
 
3.9%
d 550
 
3.5%
Other values (56) 4602
29.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15894
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3306
20.8%
e 1349
 
8.5%
i 970
 
6.1%
a 939
 
5.9%
o 912
 
5.7%
n 890
 
5.6%
t 881
 
5.5%
s 880
 
5.5%
r 615
 
3.9%
d 550
 
3.5%
Other values (56) 4602
29.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15894
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3306
20.8%
e 1349
 
8.5%
i 970
 
6.1%
a 939
 
5.9%
o 912
 
5.7%
n 890
 
5.6%
t 881
 
5.5%
s 880
 
5.5%
r 615
 
3.9%
d 550
 
3.5%
Other values (56) 4602
29.0%

Violation Memo - 17
Text

Missing 

Distinct46
Distinct (%)100.0%
Missing10630
Missing (%)99.6%
Memory size337.2 KiB
2025-04-14T23:24:35.935785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length225
Median length56
Mean length52.043478
Min length9

Characters and Unicode

Total characters2394
Distinct characters60
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st rowprovide label for food storage containers
2nd rowdo not reuse single use srticles
3rd rowleaking faucet on mop sink
4th rowRepair ventilation system above ovens
5th rowin restroom
ValueCountFrequency (%)
food 13
 
3.2%
in 13
 
3.2%
sink 10
 
2.5%
hand 9
 
2.2%
on 9
 
2.2%
for 8
 
2.0%
not 8
 
2.0%
and 8
 
2.0%
repair 8
 
2.0%
sign 6
 
1.5%
Other values (195) 316
77.5%
2025-04-14T23:24:36.319587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
367
 
15.3%
e 152
 
6.3%
o 143
 
6.0%
n 110
 
4.6%
a 95
 
4.0%
i 93
 
3.9%
s 90
 
3.8%
r 88
 
3.7%
t 84
 
3.5%
E 83
 
3.5%
Other values (50) 1089
45.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2394
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
367
 
15.3%
e 152
 
6.3%
o 143
 
6.0%
n 110
 
4.6%
a 95
 
4.0%
i 93
 
3.9%
s 90
 
3.8%
r 88
 
3.7%
t 84
 
3.5%
E 83
 
3.5%
Other values (50) 1089
45.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2394
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
367
 
15.3%
e 152
 
6.3%
o 143
 
6.0%
n 110
 
4.6%
a 95
 
4.0%
i 93
 
3.9%
s 90
 
3.8%
r 88
 
3.7%
t 84
 
3.5%
E 83
 
3.5%
Other values (50) 1089
45.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2394
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
367
 
15.3%
e 152
 
6.3%
o 143
 
6.0%
n 110
 
4.6%
a 95
 
4.0%
i 93
 
3.9%
s 90
 
3.8%
r 88
 
3.7%
t 84
 
3.5%
E 83
 
3.5%
Other values (50) 1089
45.5%
Distinct22
Distinct (%)88.0%
Missing10651
Missing (%)99.8%
Memory size335.5 KiB
2025-04-14T23:24:36.598243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length97
Median length53
Mean length46.36
Min length13

Characters and Unicode

Total characters1159
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)80.0%

Sample

1st row*36 Cloths in-use for wiping between uses stored
2nd row*44 Refuse/recyclables area maintained in good repair
3rd row*38 Thawing. under running water criteria (70 degrees Fahrenheit) or below;
4th row*45 First Aid
5th row*46 Covered waste receptacle for women's restroom
ValueCountFrequency (%)
food 7
 
3.9%
cross 4
 
2.2%
in 4
 
2.2%
45 4
 
2.2%
for 4
 
2.2%
trap 3
 
1.7%
tickets 3
 
1.7%
grease 3
 
1.7%
47 3
 
1.7%
3
 
1.7%
Other values (114) 142
78.9%
2025-04-14T23:24:36.995351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
160
13.8%
e 114
 
9.8%
i 71
 
6.1%
s 70
 
6.0%
o 69
 
6.0%
r 67
 
5.8%
a 65
 
5.6%
n 63
 
5.4%
t 61
 
5.3%
d 41
 
3.5%
Other values (53) 378
32.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1159
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
160
13.8%
e 114
 
9.8%
i 71
 
6.1%
s 70
 
6.0%
o 69
 
6.0%
r 67
 
5.8%
a 65
 
5.6%
n 63
 
5.4%
t 61
 
5.3%
d 41
 
3.5%
Other values (53) 378
32.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1159
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
160
13.8%
e 114
 
9.8%
i 71
 
6.1%
s 70
 
6.0%
o 69
 
6.0%
r 67
 
5.8%
a 65
 
5.6%
n 63
 
5.4%
t 61
 
5.3%
d 41
 
3.5%
Other values (53) 378
32.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1159
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
160
13.8%
e 114
 
9.8%
i 71
 
6.1%
s 70
 
6.0%
o 69
 
6.0%
r 67
 
5.8%
a 65
 
5.6%
n 63
 
5.4%
t 61
 
5.3%
d 41
 
3.5%
Other values (53) 378
32.6%

Violation Points - 18
Categorical

High correlation  Missing 

Distinct3
Distinct (%)12.0%
Missing10651
Missing (%)99.8%
Memory size667.3 KiB
1.0
16 
3.0
2.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters75
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 16
 
0.1%
3.0 7
 
0.1%
2.0 2
 
< 0.1%
(Missing) 10651
99.8%

Length

2025-04-14T23:24:37.108772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:37.173056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 16
64.0%
3.0 7
28.0%
2.0 2
 
8.0%

Most occurring characters

ValueCountFrequency (%)
. 25
33.3%
0 25
33.3%
1 16
21.3%
3 7
 
9.3%
2 2
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 75
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 25
33.3%
0 25
33.3%
1 16
21.3%
3 7
 
9.3%
2 2
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 75
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 25
33.3%
0 25
33.3%
1 16
21.3%
3 7
 
9.3%
2 2
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 75
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 25
33.3%
0 25
33.3%
1 16
21.3%
3 7
 
9.3%
2 2
 
2.7%

Violation Detail - 18
Text

Missing 

Distinct21
Distinct (%)87.5%
Missing10652
Missing (%)99.8%
Memory size342.2 KiB
2025-04-14T23:24:37.420448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length545
Median length307
Mean length305.875
Min length125

Characters and Unicode

Total characters7341
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)79.2%

Sample

1st row228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (d) Wiping cloths, use limitation. (2) cloths in-use for wiping counters and other equipment surfaces shall be: (A) held between uses in a chemical sanitizer solution at a concentration specified in õ228.111(n) of this title; and
2nd row228.152 Water, Plumbing, and Waste. Refuse, Recyclables, and Returnables, Facilities on the Premises. (l) Areas, enclosures, and receptacles, good repair. Storage areas, enclosures, and receptacles for refuse, recyclables, and returnables shall be maintained in good repair.
3rd row228.75 Food. Time and temperature control. (c) Thawing. Except as specified in paragraph (4) of this subsection, TCS food shall be thawed: (2) completely submerged under running water: (A) at a water temperature of 21 degrees Celsius (70 degrees Fahrenheit) or below;
4th row228.210 Poisonous or Toxic Materials. First Aid Supplies, Availability. A first aid kit shall be provided.
5th row228.152 Water, Plumbing, and Waste. Refuse, Recyclables, and Returnables, Facilities on the Premises. (h) Toilet room receptacle, covered. A toilet room used by females shall be provided with a covered receptacle for sanitary napkins.
ValueCountFrequency (%)
and 56
 
5.5%
food 40
 
3.9%
a 39
 
3.8%
of 31
 
3.1%
shall 27
 
2.7%
the 25
 
2.5%
be 18
 
1.8%
in 16
 
1.6%
equipment 14
 
1.4%
by 12
 
1.2%
Other values (330) 737
72.6%
2025-04-14T23:24:37.808585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1542
21.0%
e 625
 
8.5%
a 436
 
5.9%
i 429
 
5.8%
s 397
 
5.4%
t 382
 
5.2%
n 375
 
5.1%
o 371
 
5.1%
r 314
 
4.3%
d 236
 
3.2%
Other values (54) 2234
30.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7341
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1542
21.0%
e 625
 
8.5%
a 436
 
5.9%
i 429
 
5.8%
s 397
 
5.4%
t 382
 
5.2%
n 375
 
5.1%
o 371
 
5.1%
r 314
 
4.3%
d 236
 
3.2%
Other values (54) 2234
30.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7341
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1542
21.0%
e 625
 
8.5%
a 436
 
5.9%
i 429
 
5.8%
s 397
 
5.4%
t 382
 
5.2%
n 375
 
5.1%
o 371
 
5.1%
r 314
 
4.3%
d 236
 
3.2%
Other values (54) 2234
30.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7341
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1542
21.0%
e 625
 
8.5%
a 436
 
5.9%
i 429
 
5.8%
s 397
 
5.4%
t 382
 
5.2%
n 375
 
5.1%
o 371
 
5.1%
r 314
 
4.3%
d 236
 
3.2%
Other values (54) 2234
30.4%

Violation Memo - 18
Text

Missing 

Distinct23
Distinct (%)100.0%
Missing10653
Missing (%)99.8%
Memory size335.4 KiB
2025-04-14T23:24:38.118932image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length104
Median length53
Mean length49.695652
Min length20

Characters and Unicode

Total characters1143
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st rowstore wet cloths in sanitizer bucket
2nd rowClean and maintain garbage container (dumpster outside) free of debris and litter
3rd rowthawing method under cold running water not room temperatures
4th rowStock first aid kit.
5th rowProvide Consumer Health sign ("most recent health report available")
ValueCountFrequency (%)
and 6
 
3.3%
on 5
 
2.8%
food 5
 
2.8%
provide 4
 
2.2%
throughout 3
 
1.7%
observed 3
 
1.7%
all 3
 
1.7%
ceiling 2
 
1.1%
above 2
 
1.1%
grease 2
 
1.1%
Other values (125) 146
80.7%
2025-04-14T23:24:38.536166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158
 
13.8%
e 72
 
6.3%
o 57
 
5.0%
r 52
 
4.5%
t 50
 
4.4%
a 47
 
4.1%
E 41
 
3.6%
n 37
 
3.2%
i 34
 
3.0%
d 33
 
2.9%
Other values (48) 562
49.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1143
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
158
 
13.8%
e 72
 
6.3%
o 57
 
5.0%
r 52
 
4.5%
t 50
 
4.4%
a 47
 
4.1%
E 41
 
3.6%
n 37
 
3.2%
i 34
 
3.0%
d 33
 
2.9%
Other values (48) 562
49.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1143
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
158
 
13.8%
e 72
 
6.3%
o 57
 
5.0%
r 52
 
4.5%
t 50
 
4.4%
a 47
 
4.1%
E 41
 
3.6%
n 37
 
3.2%
i 34
 
3.0%
d 33
 
2.9%
Other values (48) 562
49.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1143
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
158
 
13.8%
e 72
 
6.3%
o 57
 
5.0%
r 52
 
4.5%
t 50
 
4.4%
a 47
 
4.1%
E 41
 
3.6%
n 37
 
3.2%
i 34
 
3.0%
d 33
 
2.9%
Other values (48) 562
49.2%
Distinct14
Distinct (%)93.3%
Missing10661
Missing (%)99.9%
Memory size334.9 KiB
2025-04-14T23:24:38.807591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length47
Mean length44.8
Min length21

Characters and Unicode

Total characters672
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)86.7%

Sample

1st row*39 Cutting surfaces.
2nd row*45 Premises shall be maintained in good repair
3rd row*39 Store equipment & utensils - avoid contamination
4th row*45 Premises shall be maintained in good repair
5th row*35 Eating food, chewing gum, drinking beverages, or using tobacco
ValueCountFrequency (%)
maintained 3
 
2.9%
3
 
2.9%
food 3
 
2.9%
45 2
 
1.9%
premises 2
 
1.9%
be 2
 
1.9%
shall 2
 
1.9%
in 2
 
1.9%
good 2
 
1.9%
surfaces 2
 
1.9%
Other values (75) 82
78.1%
2025-04-14T23:24:39.189852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93
13.8%
e 52
 
7.7%
i 52
 
7.7%
n 46
 
6.8%
o 42
 
6.2%
a 39
 
5.8%
s 36
 
5.4%
t 36
 
5.4%
r 31
 
4.6%
g 21
 
3.1%
Other values (46) 224
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 672
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
93
13.8%
e 52
 
7.7%
i 52
 
7.7%
n 46
 
6.8%
o 42
 
6.2%
a 39
 
5.8%
s 36
 
5.4%
t 36
 
5.4%
r 31
 
4.6%
g 21
 
3.1%
Other values (46) 224
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 672
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
93
13.8%
e 52
 
7.7%
i 52
 
7.7%
n 46
 
6.8%
o 42
 
6.2%
a 39
 
5.8%
s 36
 
5.4%
t 36
 
5.4%
r 31
 
4.6%
g 21
 
3.1%
Other values (46) 224
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 672
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
93
13.8%
e 52
 
7.7%
i 52
 
7.7%
n 46
 
6.8%
o 42
 
6.2%
a 39
 
5.8%
s 36
 
5.4%
t 36
 
5.4%
r 31
 
4.6%
g 21
 
3.1%
Other values (46) 224
33.3%

Violation Points - 19
Categorical

High correlation  Missing 

Distinct3
Distinct (%)20.0%
Missing10661
Missing (%)99.9%
Memory size667.3 KiB
1.0
10 
3.0
2.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters45
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 10
 
0.1%
3.0 3
 
< 0.1%
2.0 2
 
< 0.1%
(Missing) 10661
99.9%

Length

2025-04-14T23:24:39.313066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:39.382748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 10
66.7%
3.0 3
 
20.0%
2.0 2
 
13.3%

Most occurring characters

ValueCountFrequency (%)
. 15
33.3%
0 15
33.3%
1 10
22.2%
3 3
 
6.7%
2 2
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 45
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 15
33.3%
0 15
33.3%
1 10
22.2%
3 3
 
6.7%
2 2
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 45
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 15
33.3%
0 15
33.3%
1 10
22.2%
3 3
 
6.7%
2 2
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 45
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 15
33.3%
0 15
33.3%
1 10
22.2%
3 3
 
6.7%
2 2
 
4.4%

Violation Detail - 19
Text

Missing 

Distinct14
Distinct (%)93.3%
Missing10661
Missing (%)99.9%
Memory size340.5 KiB
2025-04-14T23:24:39.647920image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length815
Median length369
Mean length387.46667
Min length205

Characters and Unicode

Total characters5812
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)86.7%

Sample

1st row228.111 Equipment, Utensils, and Linens. Equipment, maintenance and operation. (b) Cutting surfaces. Surfaces such as cutting blocks and boards that are subject to scratching and scoring shall be resurfaced if they can no longer be effectively cleaned and sanitized, or discarded if they are not capable of being resurfaced.
2nd row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (a) Repairing. The physical facilities shall be maintained in good repair.
3rd row228.124 Equipment, Utensils, and Linens. Storage. (a) Equipment, utensils, linens, and single-service and single-use articles. (1) Except as specified in paragraph (4) of this subsection, cleaned equipment and utensils, laundered linens, and single-service and single-use articles shall be stored: (B) where they are not exposed to splash, dust, or other contamination; and
4th row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (a) Repairing. The physical facilities shall be maintained in good repair.
5th row228.42 Management and Personnel. Food Contamination Prevention (a) Eating, drinking, or using tobacco. (1) except as specified in paragraph (2) of this subsection, an employee shall eat, drink, or use any form of tobacco only in designated areas where the contamination of exposed food; clean equipment, utensils, and linens; unwrapped single-service and single-use articles; or other items needing protection cannot result.
ValueCountFrequency (%)
and 49
 
6.1%
of 25
 
3.1%
the 24
 
3.0%
food 23
 
2.8%
or 21
 
2.6%
be 18
 
2.2%
shall 18
 
2.2%
in 17
 
2.1%
a 17
 
2.1%
equipment 15
 
1.9%
Other values (288) 582
71.9%
2025-04-14T23:24:40.039944image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1166
20.1%
e 523
 
9.0%
i 362
 
6.2%
a 342
 
5.9%
n 340
 
5.8%
s 337
 
5.8%
t 310
 
5.3%
o 295
 
5.1%
r 247
 
4.2%
d 205
 
3.5%
Other values (54) 1685
29.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5812
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1166
20.1%
e 523
 
9.0%
i 362
 
6.2%
a 342
 
5.9%
n 340
 
5.8%
s 337
 
5.8%
t 310
 
5.3%
o 295
 
5.1%
r 247
 
4.2%
d 205
 
3.5%
Other values (54) 1685
29.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5812
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1166
20.1%
e 523
 
9.0%
i 362
 
6.2%
a 342
 
5.9%
n 340
 
5.8%
s 337
 
5.8%
t 310
 
5.3%
o 295
 
5.1%
r 247
 
4.2%
d 205
 
3.5%
Other values (54) 1685
29.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5812
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1166
20.1%
e 523
 
9.0%
i 362
 
6.2%
a 342
 
5.9%
n 340
 
5.8%
s 337
 
5.8%
t 310
 
5.3%
o 295
 
5.1%
r 247
 
4.2%
d 205
 
3.5%
Other values (54) 1685
29.0%

Violation Memo - 19
Text

Missing 

Distinct14
Distinct (%)100.0%
Missing10662
Missing (%)99.9%
Memory size334.8 KiB
2025-04-14T23:24:40.321408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length114
Median length42.5
Mean length53.5
Min length11

Characters and Unicode

Total characters749
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st rowresurface citting boards
2nd rowRepair broken floor tile, walls, baseboards, and loose faucet @ bar
3rd rowCannot store clean utensils between tables.
4th rowRepair damaged floor tiles
5th rowpersonal drinks stored next to food on prep table-designated area
ValueCountFrequency (%)
clean 5
 
4.2%
food 3
 
2.5%
not 3
 
2.5%
repair 2
 
1.7%
to 2
 
1.7%
floor 2
 
1.7%
broken 2
 
1.7%
manager 2
 
1.7%
date 2
 
1.7%
use 2
 
1.7%
Other values (90) 94
79.0%
2025-04-14T23:24:40.712034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
105
 
14.0%
e 58
 
7.7%
o 43
 
5.7%
a 33
 
4.4%
r 33
 
4.4%
n 31
 
4.1%
s 31
 
4.1%
E 30
 
4.0%
l 27
 
3.6%
t 26
 
3.5%
Other values (47) 332
44.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 749
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
105
 
14.0%
e 58
 
7.7%
o 43
 
5.7%
a 33
 
4.4%
r 33
 
4.4%
n 31
 
4.1%
s 31
 
4.1%
E 30
 
4.0%
l 27
 
3.6%
t 26
 
3.5%
Other values (47) 332
44.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 749
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
105
 
14.0%
e 58
 
7.7%
o 43
 
5.7%
a 33
 
4.4%
r 33
 
4.4%
n 31
 
4.1%
s 31
 
4.1%
E 30
 
4.0%
l 27
 
3.6%
t 26
 
3.5%
Other values (47) 332
44.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 749
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
105
 
14.0%
e 58
 
7.7%
o 43
 
5.7%
a 33
 
4.4%
r 33
 
4.4%
n 31
 
4.1%
s 31
 
4.1%
E 30
 
4.0%
l 27
 
3.6%
t 26
 
3.5%
Other values (47) 332
44.3%
Distinct7
Distinct (%)100.0%
Missing10669
Missing (%)99.9%
Memory size334.2 KiB
2025-04-14T23:24:40.914196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length49
Median length34
Mean length34
Min length20

Characters and Unicode

Total characters238
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st row*47 Other Violations
2nd row*15 Contact RTE Products w/ Bare Hands
3rd row*20 Grease Trap Tickets
4th row*44 Indoor Trash Can Cover
5th row*45 Premises shall be maintained in good repair
ValueCountFrequency (%)
47 2
 
4.9%
of 2
 
4.9%
other 1
 
2.4%
15 1
 
2.4%
contact 1
 
2.4%
rte 1
 
2.4%
violations 1
 
2.4%
products 1
 
2.4%
w 1
 
2.4%
hands 1
 
2.4%
Other values (29) 29
70.7%
2025-04-14T23:24:41.216122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35
 
14.7%
o 19
 
8.0%
e 16
 
6.7%
r 13
 
5.5%
i 13
 
5.5%
a 12
 
5.0%
n 12
 
5.0%
s 11
 
4.6%
t 10
 
4.2%
d 9
 
3.8%
Other values (37) 88
37.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 238
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
35
 
14.7%
o 19
 
8.0%
e 16
 
6.7%
r 13
 
5.5%
i 13
 
5.5%
a 12
 
5.0%
n 12
 
5.0%
s 11
 
4.6%
t 10
 
4.2%
d 9
 
3.8%
Other values (37) 88
37.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 238
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
35
 
14.7%
o 19
 
8.0%
e 16
 
6.7%
r 13
 
5.5%
i 13
 
5.5%
a 12
 
5.0%
n 12
 
5.0%
s 11
 
4.6%
t 10
 
4.2%
d 9
 
3.8%
Other values (37) 88
37.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 238
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
35
 
14.7%
o 19
 
8.0%
e 16
 
6.7%
r 13
 
5.5%
i 13
 
5.5%
a 12
 
5.0%
n 12
 
5.0%
s 11
 
4.6%
t 10
 
4.2%
d 9
 
3.8%
Other values (37) 88
37.0%

Violation Points - 20
Categorical

High correlation  Missing 

Distinct2
Distinct (%)28.6%
Missing10669
Missing (%)99.9%
Memory size667.4 KiB
1.0
3.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters21
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row3.0
3rd row3.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 4
 
< 0.1%
3.0 3
 
< 0.1%
(Missing) 10669
99.9%

Length

2025-04-14T23:24:41.326775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:41.388830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 4
57.1%
3.0 3
42.9%

Most occurring characters

ValueCountFrequency (%)
. 7
33.3%
0 7
33.3%
1 4
19.0%
3 3
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 7
33.3%
0 7
33.3%
1 4
19.0%
3 3
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 7
33.3%
0 7
33.3%
1 4
19.0%
3 3
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 7
33.3%
0 7
33.3%
1 4
19.0%
3 3
14.3%

Violation Detail - 20
Text

Missing 

Distinct6
Distinct (%)100.0%
Missing10670
Missing (%)99.9%
Memory size336.1 KiB
2025-04-14T23:24:41.667443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length521
Median length376.5
Mean length369.33333
Min length205

Characters and Unicode

Total characters2216
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowSEC. 17-3.2. ADDITIONAL REQUIREMENTS. (b) Preventing contamination by employees. (1) Preventing contamination from hands. (B) Except when washing fruits and vegetables as specified in Section Chapter 228.66 (e) of the Texas Food Establishment Rules, food employees shall avoid contact of exposed ready-to-eat food with their bare hands by use of suitable utensils such as deli tissue, spatulas, tongs, or single-use gloves.
2nd rowCh.19-126.5(c)) A producer shall sign the manifest from the transporter when a load is picked up by the transporter and shall keep a copy of all trip tickets at the producer#s business office for three years. The director may inspect these records at any reasonable time.
3rd row228.152 Water, Plumbing, and Waste. Refuse, Recyclables, and Returnables, Facilities on the Premises. (n) Covering receptacles. Receptacles and waste handling units for refuse, recyclables, and returnables shall be kept covered: (1) inside the food establishment if the receptacles and units:
4th row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (a) Repairing. The physical facilities shall be maintained in good repair.
5th row228.248 Compliance Conditions of retention, responsibilities of the permit holder. Upon acceptance of the permit issued by the regulatory authority, the permit holder in order to retain the permit shall: (11) Notify customers that a copy of the most recent establishment inspection report is available upon request by posting a sign or placard in a location in the food establishment that is conspicuous to customers or by another method acceptable to the regulatory authority.
ValueCountFrequency (%)
the 19
 
6.1%
and 12
 
3.8%
of 10
 
3.2%
food 8
 
2.6%
in 7
 
2.2%
shall 7
 
2.2%
a 7
 
2.2%
or 6
 
1.9%
by 6
 
1.9%
as 5
 
1.6%
Other values (165) 225
72.1%
2025-04-14T23:24:42.068948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
453
20.4%
e 201
 
9.1%
t 139
 
6.3%
s 128
 
5.8%
i 123
 
5.6%
a 118
 
5.3%
o 115
 
5.2%
n 100
 
4.5%
r 94
 
4.2%
l 72
 
3.2%
Other values (51) 673
30.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2216
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
453
20.4%
e 201
 
9.1%
t 139
 
6.3%
s 128
 
5.8%
i 123
 
5.6%
a 118
 
5.3%
o 115
 
5.2%
n 100
 
4.5%
r 94
 
4.2%
l 72
 
3.2%
Other values (51) 673
30.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2216
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
453
20.4%
e 201
 
9.1%
t 139
 
6.3%
s 128
 
5.8%
i 123
 
5.6%
a 118
 
5.3%
o 115
 
5.2%
n 100
 
4.5%
r 94
 
4.2%
l 72
 
3.2%
Other values (51) 673
30.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2216
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
453
20.4%
e 201
 
9.1%
t 139
 
6.3%
s 128
 
5.8%
i 123
 
5.6%
a 118
 
5.3%
o 115
 
5.2%
n 100
 
4.5%
r 94
 
4.2%
l 72
 
3.2%
Other values (51) 673
30.4%

Violation Memo - 20
Text

Missing 

Distinct7
Distinct (%)100.0%
Missing10669
Missing (%)99.9%
Memory size334.3 KiB
2025-04-14T23:24:42.304373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length79
Median length45
Mean length51.857143
Min length27

Characters and Unicode

Total characters363
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st rowPost 'choking poster' sign up for public view
2nd rowobserved employees touched rte food with bare hands tortillas
3rd rowNo grease trap ticket provided onsite.
4th rowUSE PROPER WASTE CONTAINERS
5th rowREPLACE BROKEN COVERS ON DRY INGREDIENT BINS REPAIR LOOSE FAUCET AT HAND SINK
ValueCountFrequency (%)
sign 2
 
3.3%
48 2
 
3.3%
choking 1
 
1.7%
poster 1
 
1.7%
up 1
 
1.7%
for 1
 
1.7%
public 1
 
1.7%
view 1
 
1.7%
observed 1
 
1.7%
post 1
 
1.7%
Other values (48) 48
80.0%
2025-04-14T23:24:42.633736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55
 
15.2%
o 26
 
7.2%
e 20
 
5.5%
t 16
 
4.4%
i 16
 
4.4%
r 14
 
3.9%
E 13
 
3.6%
p 12
 
3.3%
R 11
 
3.0%
s 11
 
3.0%
Other values (44) 169
46.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 363
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
55
 
15.2%
o 26
 
7.2%
e 20
 
5.5%
t 16
 
4.4%
i 16
 
4.4%
r 14
 
3.9%
E 13
 
3.6%
p 12
 
3.3%
R 11
 
3.0%
s 11
 
3.0%
Other values (44) 169
46.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 363
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
55
 
15.2%
o 26
 
7.2%
e 20
 
5.5%
t 16
 
4.4%
i 16
 
4.4%
r 14
 
3.9%
E 13
 
3.6%
p 12
 
3.3%
R 11
 
3.0%
s 11
 
3.0%
Other values (44) 169
46.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 363
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
55
 
15.2%
o 26
 
7.2%
e 20
 
5.5%
t 16
 
4.4%
i 16
 
4.4%
r 14
 
3.9%
E 13
 
3.6%
p 12
 
3.3%
R 11
 
3.0%
s 11
 
3.0%
Other values (44) 169
46.6%
Distinct7
Distinct (%)100.0%
Missing10669
Missing (%)99.9%
Memory size334.3 KiB
2025-04-14T23:24:42.841366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length100
Median length38
Mean length53
Min length20

Characters and Unicode

Total characters371
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)100.0%

Sample

1st row*46 Physical Facilities Premises
2nd row*31 Individual, disposable towels
3rd row*21 Being a certified food protection manager who has shown proficiency of required information thro
4th row*45 Premises shall be maintained in good repair
5th row*47 Other Violations
ValueCountFrequency (%)
food 3
 
5.5%
premises 2
 
3.6%
in 2
 
3.6%
facilities 1
 
1.8%
physical 1
 
1.8%
individual 1
 
1.8%
31 1
 
1.8%
towels 1
 
1.8%
21 1
 
1.8%
being 1
 
1.8%
Other values (41) 41
74.5%
2025-04-14T23:24:43.166665image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49
 
13.2%
i 31
 
8.4%
e 30
 
8.1%
o 28
 
7.5%
s 23
 
6.2%
n 21
 
5.7%
r 20
 
5.4%
a 19
 
5.1%
t 16
 
4.3%
d 11
 
3.0%
Other values (35) 123
33.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 371
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
49
 
13.2%
i 31
 
8.4%
e 30
 
8.1%
o 28
 
7.5%
s 23
 
6.2%
n 21
 
5.7%
r 20
 
5.4%
a 19
 
5.1%
t 16
 
4.3%
d 11
 
3.0%
Other values (35) 123
33.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 371
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
49
 
13.2%
i 31
 
8.4%
e 30
 
8.1%
o 28
 
7.5%
s 23
 
6.2%
n 21
 
5.7%
r 20
 
5.4%
a 19
 
5.1%
t 16
 
4.3%
d 11
 
3.0%
Other values (35) 123
33.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 371
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
49
 
13.2%
i 31
 
8.4%
e 30
 
8.1%
o 28
 
7.5%
s 23
 
6.2%
n 21
 
5.7%
r 20
 
5.4%
a 19
 
5.1%
t 16
 
4.3%
d 11
 
3.0%
Other values (35) 123
33.2%

Violation Points - 21
Categorical

High correlation  Missing 

Distinct3
Distinct (%)42.9%
Missing10669
Missing (%)99.9%
Memory size667.4 KiB
1.0
2.0
3.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters21
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)14.3%

Sample

1st row1.0
2nd row2.0
3rd row2.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.0 4
 
< 0.1%
2.0 2
 
< 0.1%
3.0 1
 
< 0.1%
(Missing) 10669
99.9%

Length

2025-04-14T23:24:43.279298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:43.353156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 4
57.1%
2.0 2
28.6%
3.0 1
 
14.3%

Most occurring characters

ValueCountFrequency (%)
. 7
33.3%
0 7
33.3%
1 4
19.0%
2 2
 
9.5%
3 1
 
4.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 7
33.3%
0 7
33.3%
1 4
19.0%
2 2
 
9.5%
3 1
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 7
33.3%
0 7
33.3%
1 4
19.0%
2 2
 
9.5%
3 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 7
33.3%
0 7
33.3%
1 4
19.0%
2 2
 
9.5%
3 1
 
4.8%

Violation Detail - 21
Text

Missing 

Distinct6
Distinct (%)100.0%
Missing10670
Missing (%)99.9%
Memory size335.9 KiB
2025-04-14T23:24:43.642993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length592
Median length294
Mean length344.33333
Min length205

Characters and Unicode

Total characters2066
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (h) Cleaning of Plumbing Fixtures. Plumbing fixtures such as handwashing sinks, toilets, and urinals shall be cleaned as often as necessary to keep them clean.
2nd row228.175 Physical Facilities. Handwashing Sinks. (c) Hand drying provision. Each handwashing lavatory or group of adjacent lavatories shall be provided with: (1) individual, disposable towels;
3rd row228.32 Management and Personnel. Knowledge. Based on the risks inherent to the food operation, during inspections and upon request the person in charge shall demonstrate to the regulatory authority knowledge of foodborne disease prevention, application of the Hazard Analysis Critical Control Point principles, and the requirements of this rule. The person in charge shall demonstrate this knowledge by: (2) being a certified food protection manager who has shown proficiency of required information through passing a test that is part of an Accredited Program; or
4th row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (a) Repairing. The physical facilities shall be maintained in good repair.
5th row228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (b) In-use utensils, between-use storage. During pauses in food preparation or dispensing, food preparation and dispensing utensils shall be stored: (2) in food that is not time/temperature controlled for safety (TCS) with their handles above the top of the food within containers or equipment that can be closed, such as bins of sugar, flour, or cinnamon;
ValueCountFrequency (%)
of 10
 
3.6%
the 10
 
3.6%
and 9
 
3.3%
food 9
 
3.3%
shall 7
 
2.5%
be 6
 
2.2%
or 6
 
2.2%
in 5
 
1.8%
to 4
 
1.5%
facilities 4
 
1.5%
Other values (149) 205
74.5%
2025-04-14T23:24:44.053032image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
430
20.8%
e 169
 
8.2%
i 129
 
6.2%
s 120
 
5.8%
n 118
 
5.7%
o 117
 
5.7%
a 111
 
5.4%
t 108
 
5.2%
r 95
 
4.6%
l 66
 
3.2%
Other values (49) 603
29.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2066
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
430
20.8%
e 169
 
8.2%
i 129
 
6.2%
s 120
 
5.8%
n 118
 
5.7%
o 117
 
5.7%
a 111
 
5.4%
t 108
 
5.2%
r 95
 
4.6%
l 66
 
3.2%
Other values (49) 603
29.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2066
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
430
20.8%
e 169
 
8.2%
i 129
 
6.2%
s 120
 
5.8%
n 118
 
5.7%
o 117
 
5.7%
a 111
 
5.4%
t 108
 
5.2%
r 95
 
4.6%
l 66
 
3.2%
Other values (49) 603
29.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2066
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
430
20.8%
e 169
 
8.2%
i 129
 
6.2%
s 120
 
5.8%
n 118
 
5.7%
o 117
 
5.7%
a 111
 
5.4%
t 108
 
5.2%
r 95
 
4.6%
l 66
 
3.2%
Other values (49) 603
29.2%

Violation Memo - 21
Text

Missing 

Distinct6
Distinct (%)100.0%
Missing10670
Missing (%)99.9%
Memory size334.1 KiB
2025-04-14T23:24:44.258217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length54
Median length43
Mean length40.166667
Min length20

Characters and Unicode

Total characters241
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st rowRepair urinals in men's restroom
2nd rowprovide paper towels
3rd rowNo one has a food manager certification on site.
4th rowPROVIDE PEST CONTROL RECORDS- INSECTS/ROACHES OBSERVED
5th rowuse utensils with handle to scoop food
ValueCountFrequency (%)
provide 2
 
5.1%
food 2
 
5.1%
in 1
 
2.6%
urinals 1
 
2.6%
repair 1
 
2.6%
restroom 1
 
2.6%
men's 1
 
2.6%
towels 1
 
2.6%
paper 1
 
2.6%
no 1
 
2.6%
Other values (27) 27
69.2%
2025-04-14T23:24:44.649850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33
 
13.7%
o 18
 
7.5%
e 17
 
7.1%
r 13
 
5.4%
a 13
 
5.4%
s 13
 
5.4%
i 12
 
5.0%
n 11
 
4.6%
t 10
 
4.1%
p 7
 
2.9%
Other values (35) 94
39.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 241
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
33
 
13.7%
o 18
 
7.5%
e 17
 
7.1%
r 13
 
5.4%
a 13
 
5.4%
s 13
 
5.4%
i 12
 
5.0%
n 11
 
4.6%
t 10
 
4.1%
p 7
 
2.9%
Other values (35) 94
39.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 241
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
33
 
13.7%
o 18
 
7.5%
e 17
 
7.1%
r 13
 
5.4%
a 13
 
5.4%
s 13
 
5.4%
i 12
 
5.0%
n 11
 
4.6%
t 10
 
4.1%
p 7
 
2.9%
Other values (35) 94
39.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 241
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
33
 
13.7%
o 18
 
7.5%
e 17
 
7.1%
r 13
 
5.4%
a 13
 
5.4%
s 13
 
5.4%
i 12
 
5.0%
n 11
 
4.6%
t 10
 
4.1%
p 7
 
2.9%
Other values (35) 94
39.0%
Distinct3
Distinct (%)100.0%
Missing10673
Missing (%)> 99.9%
Memory size334.0 KiB
2025-04-14T23:24:44.854539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length50
Median length49
Mean length48.666667
Min length47

Characters and Unicode

Total characters146
Distinct characters32
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row*24 Food Labeling- with common name of the food
2nd row*47 Conditions of Permit-in use of food equipment
3rd row*24 Food Label- manufacture/packer/distrubtor name
ValueCountFrequency (%)
food 4
18.2%
of 3
13.6%
24 2
 
9.1%
name 2
 
9.1%
labeling 1
 
4.5%
common 1
 
4.5%
with 1
 
4.5%
the 1
 
4.5%
47 1
 
4.5%
conditions 1
 
4.5%
Other values (5) 5
22.7%
2025-04-14T23:24:45.181342image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
13.0%
o 16
 
11.0%
e 11
 
7.5%
n 9
 
6.2%
i 8
 
5.5%
t 8
 
5.5%
m 7
 
4.8%
a 7
 
4.8%
d 6
 
4.1%
f 6
 
4.1%
Other values (22) 49
33.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 146
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
19
 
13.0%
o 16
 
11.0%
e 11
 
7.5%
n 9
 
6.2%
i 8
 
5.5%
t 8
 
5.5%
m 7
 
4.8%
a 7
 
4.8%
d 6
 
4.1%
f 6
 
4.1%
Other values (22) 49
33.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 146
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
19
 
13.0%
o 16
 
11.0%
e 11
 
7.5%
n 9
 
6.2%
i 8
 
5.5%
t 8
 
5.5%
m 7
 
4.8%
a 7
 
4.8%
d 6
 
4.1%
f 6
 
4.1%
Other values (22) 49
33.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 146
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
19
 
13.0%
o 16
 
11.0%
e 11
 
7.5%
n 9
 
6.2%
i 8
 
5.5%
t 8
 
5.5%
m 7
 
4.8%
a 7
 
4.8%
d 6
 
4.1%
f 6
 
4.1%
Other values (22) 49
33.6%

Violation Points - 22
Categorical

High correlation  Missing 

Distinct2
Distinct (%)66.7%
Missing10673
Missing (%)> 99.9%
Memory size667.4 KiB
2.0
1.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st row2.0
2nd row1.0
3rd row2.0

Common Values

ValueCountFrequency (%)
2.0 2
 
< 0.1%
1.0 1
 
< 0.1%
(Missing) 10673
> 99.9%

Length

2025-04-14T23:24:45.342120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:45.431804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2.0 2
66.7%
1.0 1
33.3%

Most occurring characters

ValueCountFrequency (%)
. 3
33.3%
0 3
33.3%
2 2
22.2%
1 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 3
33.3%
0 3
33.3%
2 2
22.2%
1 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 3
33.3%
0 3
33.3%
2 2
22.2%
1 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 3
33.3%
0 3
33.3%
2 2
22.2%
1 1
 
11.1%

Violation Detail - 22
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing10673
Missing (%)> 99.9%
Memory size334.7 KiB
2025-04-14T23:24:45.704563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length521
Median length217
Mean length311
Min length195

Characters and Unicode

Total characters933
Distinct characters42
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row228.79 Food. Labeling. (a) Food labels. (2) Label information shall include: (A) the common name of the food, or absent a common name, an adequately descriptive identity statement;
2nd row228.248 Compliance Conditions of retention, responsibilities of the permit holder. Upon acceptance of the permit issued by the regulatory authority, the permit holder in order to retain the permit shall: (11) Notify customers that a copy of the most recent establishment inspection report is available upon request by posting a sign or placard in a location in the food establishment that is conspicuous to customers or by another method acceptable to the regulatory authority.
3rd row228.79 Food. Labeling. (a) Food labels. (2) Label information shall include: (D) the name and place of business of the manufacturer, packer, or distributor; and
ValueCountFrequency (%)
the 12
 
9.4%
a 7
 
5.5%
of 7
 
5.5%
food 6
 
4.7%
permit 4
 
3.1%
or 4
 
3.1%
to 3
 
2.4%
name 3
 
2.4%
by 3
 
2.4%
shall 3
 
2.4%
Other values (56) 75
59.1%
2025-04-14T23:24:46.156305image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
240
25.7%
e 70
 
7.5%
t 65
 
7.0%
o 63
 
6.8%
a 52
 
5.6%
i 46
 
4.9%
n 44
 
4.7%
r 37
 
4.0%
s 35
 
3.8%
l 31
 
3.3%
Other values (32) 250
26.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 933
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
240
25.7%
e 70
 
7.5%
t 65
 
7.0%
o 63
 
6.8%
a 52
 
5.6%
i 46
 
4.9%
n 44
 
4.7%
r 37
 
4.0%
s 35
 
3.8%
l 31
 
3.3%
Other values (32) 250
26.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 933
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
240
25.7%
e 70
 
7.5%
t 65
 
7.0%
o 63
 
6.8%
a 52
 
5.6%
i 46
 
4.9%
n 44
 
4.7%
r 37
 
4.0%
s 35
 
3.8%
l 31
 
3.3%
Other values (32) 250
26.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 933
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
240
25.7%
e 70
 
7.5%
t 65
 
7.0%
o 63
 
6.8%
a 52
 
5.6%
i 46
 
4.9%
n 44
 
4.7%
r 37
 
4.0%
s 35
 
3.8%
l 31
 
3.3%
Other values (32) 250
26.8%

Violation Memo - 22
Text

Missing 

Distinct3
Distinct (%)100.0%
Missing10673
Missing (%)> 99.9%
Memory size334.0 KiB
2025-04-14T23:24:46.413500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length75
Median length34
Mean length44.333333
Min length24

Characters and Unicode

Total characters133
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st rowLabel all packaged food.
2nd rowPOST SIGN THAT STATES: MOST RECENT HEALTH REPORT IS AVAILABLE UPON REQUEST.
3rd rowprovide manufacture name for salsa
ValueCountFrequency (%)
label 1
 
4.8%
all 1
 
4.8%
packaged 1
 
4.8%
food 1
 
4.8%
post 1
 
4.8%
sign 1
 
4.8%
that 1
 
4.8%
states 1
 
4.8%
most 1
 
4.8%
recent 1
 
4.8%
Other values (11) 11
52.4%
2025-04-14T23:24:46.806711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
13.5%
T 10
 
7.5%
a 9
 
6.8%
E 8
 
6.0%
S 7
 
5.3%
A 6
 
4.5%
e 5
 
3.8%
L 4
 
3.0%
O 4
 
3.0%
o 4
 
3.0%
Other values (30) 58
43.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 133
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
18
 
13.5%
T 10
 
7.5%
a 9
 
6.8%
E 8
 
6.0%
S 7
 
5.3%
A 6
 
4.5%
e 5
 
3.8%
L 4
 
3.0%
O 4
 
3.0%
o 4
 
3.0%
Other values (30) 58
43.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 133
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
18
 
13.5%
T 10
 
7.5%
a 9
 
6.8%
E 8
 
6.0%
S 7
 
5.3%
A 6
 
4.5%
e 5
 
3.8%
L 4
 
3.0%
O 4
 
3.0%
o 4
 
3.0%
Other values (30) 58
43.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 133
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
18
 
13.5%
T 10
 
7.5%
a 9
 
6.8%
E 8
 
6.0%
S 7
 
5.3%
A 6
 
4.5%
e 5
 
3.8%
L 4
 
3.0%
O 4
 
3.0%
o 4
 
3.0%
Other values (30) 58
43.6%

Violation Description - 23
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing10675
Missing (%)> 99.9%
Memory size333.8 KiB
2025-04-14T23:24:47.024648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters42
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row*28 Date marking > 24 hrs,on site,temp 41F
ValueCountFrequency (%)
28 1
12.5%
date 1
12.5%
marking 1
12.5%
1
12.5%
24 1
12.5%
hrs,on 1
12.5%
site,temp 1
12.5%
41f 1
12.5%
2025-04-14T23:24:47.256349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7
16.7%
t 3
 
7.1%
e 3
 
7.1%
a 2
 
4.8%
r 2
 
4.8%
m 2
 
4.8%
2 2
 
4.8%
n 2
 
4.8%
, 2
 
4.8%
s 2
 
4.8%
Other values (13) 15
35.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7
16.7%
t 3
 
7.1%
e 3
 
7.1%
a 2
 
4.8%
r 2
 
4.8%
m 2
 
4.8%
2 2
 
4.8%
n 2
 
4.8%
, 2
 
4.8%
s 2
 
4.8%
Other values (13) 15
35.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7
16.7%
t 3
 
7.1%
e 3
 
7.1%
a 2
 
4.8%
r 2
 
4.8%
m 2
 
4.8%
2 2
 
4.8%
n 2
 
4.8%
, 2
 
4.8%
s 2
 
4.8%
Other values (13) 15
35.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7
16.7%
t 3
 
7.1%
e 3
 
7.1%
a 2
 
4.8%
r 2
 
4.8%
m 2
 
4.8%
2 2
 
4.8%
n 2
 
4.8%
, 2
 
4.8%
s 2
 
4.8%
Other values (13) 15
35.7%

Violation Points - 23
Categorical

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing10675
Missing (%)> 99.9%
Memory size667.4 KiB
2.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2.0

Common Values

ValueCountFrequency (%)
2.0 1
 
< 0.1%
(Missing) 10675
> 99.9%

Length

2025-04-14T23:24:47.363888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:47.419451image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2.0 1
100.0%

Most occurring characters

ValueCountFrequency (%)
2 1
33.3%
. 1
33.3%
0 1
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 1
33.3%
. 1
33.3%
0 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 1
33.3%
. 1
33.3%
0 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 1
33.3%
. 1
33.3%
0 1
33.3%

Violation Detail - 23
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing10675
Missing (%)> 99.9%
Memory size334.6 KiB
2025-04-14T23:24:47.615523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length815
Median length815
Mean length815
Min length815

Characters and Unicode

Total characters815
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row228.75 Food. Time and temperature control. (g) Ready-to-eat, TCS food, date marking. (2) Except as specified in paragraphs (5) - (7) of this subsection, refrigerated, ready-to-eat, time/temperature controlled for safety food prepared and packaged by a food processing plant shall be clearly marked, at the time the original container is opened in a food establishment and held at a temperature of 41 degrees Fahrenheit (5 degrees Celsius) or less if the food is held for more than 24 hours, to indicate the date or day by which the food shall be consumed on the premises, sold, or discarded, based on the temperature and time combinations specified in paragraph (1) of this subsection: (A) the day the original container is opened in the food establishment shall be counted as day 1; and
ValueCountFrequency (%)
the 10
 
7.6%
food 8
 
6.1%
and 5
 
3.8%
in 4
 
3.1%
a 4
 
3.1%
temperature 3
 
2.3%
time 3
 
2.3%
day 3
 
2.3%
or 3
 
2.3%
is 3
 
2.3%
Other values (61) 85
64.9%
2025-04-14T23:24:47.934368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
158
19.4%
e 83
 
10.2%
a 55
 
6.7%
t 51
 
6.3%
o 49
 
6.0%
d 41
 
5.0%
r 40
 
4.9%
i 40
 
4.9%
s 38
 
4.7%
n 35
 
4.3%
Other values (34) 225
27.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 815
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
158
19.4%
e 83
 
10.2%
a 55
 
6.7%
t 51
 
6.3%
o 49
 
6.0%
d 41
 
5.0%
r 40
 
4.9%
i 40
 
4.9%
s 38
 
4.7%
n 35
 
4.3%
Other values (34) 225
27.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 815
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
158
19.4%
e 83
 
10.2%
a 55
 
6.7%
t 51
 
6.3%
o 49
 
6.0%
d 41
 
5.0%
r 40
 
4.9%
i 40
 
4.9%
s 38
 
4.7%
n 35
 
4.3%
Other values (34) 225
27.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 815
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
158
19.4%
e 83
 
10.2%
a 55
 
6.7%
t 51
 
6.3%
o 49
 
6.0%
d 41
 
5.0%
r 40
 
4.9%
i 40
 
4.9%
s 38
 
4.7%
n 35
 
4.3%
Other values (34) 225
27.6%

Violation Memo - 23
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing10675
Missing (%)> 99.9%
Memory size333.8 KiB
2025-04-14T23:24:48.071748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length42
Median length42
Mean length42
Min length42

Characters and Unicode

Total characters42
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowclearly date mark TCS food for 7 days only
ValueCountFrequency (%)
clearly 1
11.1%
date 1
11.1%
mark 1
11.1%
tcs 1
11.1%
food 1
11.1%
for 1
11.1%
7 1
11.1%
days 1
11.1%
only 1
11.1%
2025-04-14T23:24:48.295053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8
19.0%
a 4
9.5%
o 4
9.5%
d 3
 
7.1%
y 3
 
7.1%
l 3
 
7.1%
r 3
 
7.1%
f 2
 
4.8%
e 2
 
4.8%
c 1
 
2.4%
Other values (9) 9
21.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8
19.0%
a 4
9.5%
o 4
9.5%
d 3
 
7.1%
y 3
 
7.1%
l 3
 
7.1%
r 3
 
7.1%
f 2
 
4.8%
e 2
 
4.8%
c 1
 
2.4%
Other values (9) 9
21.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8
19.0%
a 4
9.5%
o 4
9.5%
d 3
 
7.1%
y 3
 
7.1%
l 3
 
7.1%
r 3
 
7.1%
f 2
 
4.8%
e 2
 
4.8%
c 1
 
2.4%
Other values (9) 9
21.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8
19.0%
a 4
9.5%
o 4
9.5%
d 3
 
7.1%
y 3
 
7.1%
l 3
 
7.1%
r 3
 
7.1%
f 2
 
4.8%
e 2
 
4.8%
c 1
 
2.4%
Other values (9) 9
21.4%

Violation Description - 24
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing10675
Missing (%)> 99.9%
Memory size333.8 KiB
2025-04-14T23:24:48.430191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row*45 Drying Mops-air dry
ValueCountFrequency (%)
45 1
25.0%
drying 1
25.0%
mops-air 1
25.0%
dry 1
25.0%
2025-04-14T23:24:48.650335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3
13.0%
r 3
13.0%
y 2
 
8.7%
i 2
 
8.7%
* 1
 
4.3%
D 1
 
4.3%
5 1
 
4.3%
4 1
 
4.3%
n 1
 
4.3%
g 1
 
4.3%
Other values (7) 7
30.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3
13.0%
r 3
13.0%
y 2
 
8.7%
i 2
 
8.7%
* 1
 
4.3%
D 1
 
4.3%
5 1
 
4.3%
4 1
 
4.3%
n 1
 
4.3%
g 1
 
4.3%
Other values (7) 7
30.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3
13.0%
r 3
13.0%
y 2
 
8.7%
i 2
 
8.7%
* 1
 
4.3%
D 1
 
4.3%
5 1
 
4.3%
4 1
 
4.3%
n 1
 
4.3%
g 1
 
4.3%
Other values (7) 7
30.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3
13.0%
r 3
13.0%
y 2
 
8.7%
i 2
 
8.7%
* 1
 
4.3%
D 1
 
4.3%
5 1
 
4.3%
4 1
 
4.3%
n 1
 
4.3%
g 1
 
4.3%
Other values (7) 7
30.4%

Violation Points - 24
Categorical

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing10675
Missing (%)> 99.9%
Memory size667.4 KiB
1.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row1.0

Common Values

ValueCountFrequency (%)
1.0 1
 
< 0.1%
(Missing) 10675
> 99.9%

Length

2025-04-14T23:24:48.746114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:48.802069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.0 1
100.0%

Most occurring characters

ValueCountFrequency (%)
1 1
33.3%
. 1
33.3%
0 1
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1
33.3%
. 1
33.3%
0 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1
33.3%
. 1
33.3%
0 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1
33.3%
. 1
33.3%
0 1
33.3%

Violation Detail - 24
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing10675
Missing (%)> 99.9%
Memory size334.0 KiB
2025-04-14T23:24:48.951193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length268
Median length268
Mean length268
Min length268

Characters and Unicode

Total characters268
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (f) Drying mops. After use, mops shall be placed in a position that allows them to air-dry without soiling walls, equipment, or supplies.
ValueCountFrequency (%)
equipment 2
 
5.7%
mops 2
 
5.7%
228.186 1
 
2.9%
premises 1
 
2.9%
physical 1
 
2.9%
buildings 1
 
2.9%
systems 1
 
2.9%
rooms 1
 
2.9%
facilities 1
 
2.9%
fixtures 1
 
2.9%
Other values (23) 23
65.7%
2025-04-14T23:24:49.230298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
20.1%
s 22
 
8.2%
i 21
 
7.8%
e 18
 
6.7%
t 14
 
5.2%
l 13
 
4.9%
a 12
 
4.5%
o 11
 
4.1%
, 10
 
3.7%
r 9
 
3.4%
Other values (27) 84
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 268
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
54
20.1%
s 22
 
8.2%
i 21
 
7.8%
e 18
 
6.7%
t 14
 
5.2%
l 13
 
4.9%
a 12
 
4.5%
o 11
 
4.1%
, 10
 
3.7%
r 9
 
3.4%
Other values (27) 84
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 268
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
54
20.1%
s 22
 
8.2%
i 21
 
7.8%
e 18
 
6.7%
t 14
 
5.2%
l 13
 
4.9%
a 12
 
4.5%
o 11
 
4.1%
, 10
 
3.7%
r 9
 
3.4%
Other values (27) 84
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 268
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
54
20.1%
s 22
 
8.2%
i 21
 
7.8%
e 18
 
6.7%
t 14
 
5.2%
l 13
 
4.9%
a 12
 
4.5%
o 11
 
4.1%
, 10
 
3.7%
r 9
 
3.4%
Other values (27) 84
31.3%

Violation Memo - 24
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing10675
Missing (%)> 99.9%
Memory size333.8 KiB
2025-04-14T23:24:49.348009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters13
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowmops need dry
ValueCountFrequency (%)
mops 1
33.3%
need 1
33.3%
dry 1
33.3%
2025-04-14T23:24:49.553505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2
15.4%
2
15.4%
d 2
15.4%
m 1
7.7%
o 1
7.7%
p 1
7.7%
n 1
7.7%
s 1
7.7%
r 1
7.7%
y 1
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2
15.4%
2
15.4%
d 2
15.4%
m 1
7.7%
o 1
7.7%
p 1
7.7%
n 1
7.7%
s 1
7.7%
r 1
7.7%
y 1
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2
15.4%
2
15.4%
d 2
15.4%
m 1
7.7%
o 1
7.7%
p 1
7.7%
n 1
7.7%
s 1
7.7%
r 1
7.7%
y 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2
15.4%
2
15.4%
d 2
15.4%
m 1
7.7%
o 1
7.7%
p 1
7.7%
n 1
7.7%
s 1
7.7%
r 1
7.7%
y 1
7.7%

Violation Description - 25
Unsupported

Missing  Rejected  Unsupported 

Missing10676
Missing (%)100.0%
Memory size83.5 KiB

Violation Points - 25
Unsupported

Missing  Rejected  Unsupported 

Missing10676
Missing (%)100.0%
Memory size83.5 KiB

Violation Detail - 25
Unsupported

Missing  Rejected  Unsupported 

Missing10676
Missing (%)100.0%
Memory size83.5 KiB

Violation Memo - 25
Unsupported

Missing  Rejected  Unsupported 

Missing10676
Missing (%)100.0%
Memory size83.5 KiB

Inspection Month
Categorical

High correlation 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size677.8 KiB
Mar 2023
1034 
Jan 2024
975 
Feb 2023
952 
Jan 2023
894 
May 2023
836 
Other values (9)
5985 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters85408
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAug 2023
2nd rowMar 2023
3rd rowJul 2023
4th rowJun 2023
5th rowJul 2023

Common Values

ValueCountFrequency (%)
Mar 2023 1034
9.7%
Jan 2024 975
9.1%
Feb 2023 952
8.9%
Jan 2023 894
 
8.4%
May 2023 836
 
7.8%
Jul 2023 808
 
7.6%
Apr 2023 776
 
7.3%
Dec 2023 720
 
6.7%
Sep 2023 713
 
6.7%
Nov 2023 688
 
6.4%
Other values (4) 2280
21.4%

Length

2025-04-14T23:24:49.651014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023 9110
42.7%
jan 1869
 
8.8%
2024 1566
 
7.3%
feb 1543
 
7.2%
mar 1034
 
4.8%
may 836
 
3.9%
jul 808
 
3.8%
apr 776
 
3.6%
dec 720
 
3.4%
sep 713
 
3.3%
Other values (4) 2377
 
11.1%

Most occurring characters

ValueCountFrequency (%)
2 21352
25.0%
10676
12.5%
0 10676
12.5%
3 9110
10.7%
a 3739
 
4.4%
J 3314
 
3.9%
e 2976
 
3.5%
n 2506
 
2.9%
u 2131
 
2.5%
M 1870
 
2.2%
Other values (17) 17058
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 85408
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 21352
25.0%
10676
12.5%
0 10676
12.5%
3 9110
10.7%
a 3739
 
4.4%
J 3314
 
3.9%
e 2976
 
3.5%
n 2506
 
2.9%
u 2131
 
2.5%
M 1870
 
2.2%
Other values (17) 17058
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 85408
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 21352
25.0%
10676
12.5%
0 10676
12.5%
3 9110
10.7%
a 3739
 
4.4%
J 3314
 
3.9%
e 2976
 
3.5%
n 2506
 
2.9%
u 2131
 
2.5%
M 1870
 
2.2%
Other values (17) 17058
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 85408
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 21352
25.0%
10676
12.5%
0 10676
12.5%
3 9110
10.7%
a 3739
 
4.4%
J 3314
 
3.9%
e 2976
 
3.5%
n 2506
 
2.9%
u 2131
 
2.5%
M 1870
 
2.2%
Other values (17) 17058
20.0%

Inspection Year
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size657.0 KiB
FY2023
7336 
FY2024
3340 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters64056
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFY2023
2nd rowFY2023
3rd rowFY2023
4th rowFY2023
5th rowFY2023

Common Values

ValueCountFrequency (%)
FY2023 7336
68.7%
FY2024 3340
31.3%

Length

2025-04-14T23:24:49.741483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-14T23:24:49.801432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
fy2023 7336
68.7%
fy2024 3340
31.3%

Most occurring characters

ValueCountFrequency (%)
2 21352
33.3%
F 10676
16.7%
Y 10676
16.7%
0 10676
16.7%
3 7336
 
11.5%
4 3340
 
5.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 64056
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 21352
33.3%
F 10676
16.7%
Y 10676
16.7%
0 10676
16.7%
3 7336
 
11.5%
4 3340
 
5.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 64056
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 21352
33.3%
F 10676
16.7%
Y 10676
16.7%
0 10676
16.7%
3 7336
 
11.5%
4 3340
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 64056
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 21352
33.3%
F 10676
16.7%
Y 10676
16.7%
0 10676
16.7%
3 7336
 
11.5%
4 3340
 
5.2%
Distinct7760
Distinct (%)72.7%
Missing0
Missing (%)0.0%
Memory size908.9 KiB
2025-04-14T23:24:50.113199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length73
Median length62
Mean length30.166729
Min length10

Characters and Unicode

Total characters322060
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5850 ?
Unique (%)54.8%

Sample

1st row3100 GRAND AVE
2nd row10677 E NORTHWEST HWY #300 (32.86516, -96.70169)
3rd row10720 PRESTON RD #1101
4th row6777 W KIEST BLVD
5th row1000 COMMERCE ST
ValueCountFrequency (%)
rd 2841
 
5.5%
ave 1653
 
3.2%
st 1594
 
3.1%
w 1257
 
2.4%
ln 1157
 
2.2%
blvd 1077
 
2.1%
s 1028
 
2.0%
n 973
 
1.9%
dr 720
 
1.4%
e 512
 
1.0%
Other values (10177) 38944
75.2%
2025-04-14T23:24:50.636075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36272
 
11.3%
0 16865
 
5.2%
1 16395
 
5.1%
2 15446
 
4.8%
9 15043
 
4.7%
3 14468
 
4.5%
6 12368
 
3.8%
8 12106
 
3.8%
R 11310
 
3.5%
7 11206
 
3.5%
Other values (35) 160581
49.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 322060
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
36272
 
11.3%
0 16865
 
5.2%
1 16395
 
5.1%
2 15446
 
4.8%
9 15043
 
4.7%
3 14468
 
4.5%
6 12368
 
3.8%
8 12106
 
3.8%
R 11310
 
3.5%
7 11206
 
3.5%
Other values (35) 160581
49.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 322060
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
36272
 
11.3%
0 16865
 
5.2%
1 16395
 
5.1%
2 15446
 
4.8%
9 15043
 
4.7%
3 14468
 
4.5%
6 12368
 
3.8%
8 12106
 
3.8%
R 11310
 
3.5%
7 11206
 
3.5%
Other values (35) 160581
49.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 322060
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
36272
 
11.3%
0 16865
 
5.2%
1 16395
 
5.1%
2 15446
 
4.8%
9 15043
 
4.7%
3 14468
 
4.5%
6 12368
 
3.8%
8 12106
 
3.8%
R 11310
 
3.5%
7 11206
 
3.5%
Other values (35) 160581
49.9%

Interactions

2025-04-14T23:23:31.418315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-14T23:23:31.018319image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-14T23:23:31.532249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-14T23:23:31.122345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-04-14T23:24:50.767148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Inspection MonthInspection ScoreInspection TypeInspection YearStreet DirectionStreet NumberStreet TypeViolation Points - 1Violation Points - 10Violation Points - 11Violation Points - 12Violation Points - 13Violation Points - 14Violation Points - 15Violation Points - 16Violation Points - 17Violation Points - 18Violation Points - 19Violation Points - 2Violation Points - 20Violation Points - 21Violation Points - 22Violation Points - 3Violation Points - 4Violation Points - 5Violation Points - 6Violation Points - 7Violation Points - 8Violation Points - 9
Inspection Month1.0000.0580.0820.9990.1020.0770.0790.0930.0870.1140.1400.1510.0000.1570.0000.0000.0000.0000.0740.0000.0000.0000.0550.0560.0300.0690.0810.1110.061
Inspection Score0.0581.0000.1310.0460.0650.0090.0470.1210.0660.0000.1030.0000.1320.0000.1730.3450.0000.1710.2270.0000.0001.0000.2500.2790.2150.1630.1800.1680.098
Inspection Type0.0820.1311.0000.0290.0220.0320.0450.0170.0800.0390.0000.0000.0550.0000.0000.0000.0001.0000.0311.0001.0001.0000.0090.0000.0230.0460.0320.0580.068
Inspection Year0.9990.0460.0291.0000.1000.0790.1070.0620.0000.0440.0000.0000.0000.0180.2130.0000.4540.0000.0420.0000.0001.0000.0630.0290.0000.0050.0000.0320.015
Street Direction0.1020.0650.0220.1001.0000.2500.4390.0430.0000.0000.0490.1080.1160.0000.0600.0000.0000.0000.0391.0001.0001.0000.0170.0000.0320.0000.0000.0000.036
Street Number0.0770.0090.0320.0790.2501.0000.2770.0560.0350.0410.0000.0000.0000.0000.0930.0000.0000.0000.0810.8940.5001.0000.0700.0490.0220.0490.0470.0580.052
Street Type0.0790.0470.0450.1070.4390.2771.0000.0620.0500.1030.0340.0950.0830.0000.0000.1810.0870.1910.0610.0000.0001.0000.0560.0550.0530.0650.0000.0400.061
Violation Points - 10.0930.1210.0170.0620.0430.0560.0621.0000.2210.1920.1940.2050.2950.2740.2580.4730.2450.3930.2550.6710.3951.0000.1380.1270.1520.1490.1760.1730.203
Violation Points - 100.0870.0660.0800.0000.0000.0350.0500.2211.0000.1490.1440.1070.0490.0440.1650.1450.2640.1920.2170.0000.3951.0000.1770.1480.1530.1150.0880.1070.151
Violation Points - 110.1140.0000.0390.0440.0000.0410.1030.1920.1491.0000.1530.1260.1410.1200.2020.0000.2720.0000.1790.0000.0001.0000.1900.1630.1610.0780.0590.0350.117
Violation Points - 120.1400.1030.0000.0000.0490.0000.0340.1940.1440.1531.0000.2150.2070.1740.0000.0000.0570.0000.1880.0000.0001.0000.1590.1600.1760.1240.1170.1130.054
Violation Points - 130.1510.0000.0000.0000.1080.0000.0950.2050.1070.1260.2151.0000.2450.2080.0320.2680.3950.3140.2080.0000.3161.0000.2590.2690.2810.1670.1760.1530.141
Violation Points - 140.0000.1320.0550.0000.1160.0000.0830.2950.0490.1410.2070.2451.0000.2050.0000.3860.0570.0000.1980.0000.0000.0000.2800.1310.2320.2120.2040.2250.181
Violation Points - 150.1570.0000.0000.0180.0000.0000.0000.2740.0440.1200.1740.2080.2051.0000.2090.1710.1440.5400.1820.0000.0000.0000.2640.1570.1710.2610.1440.2270.194
Violation Points - 160.0000.1730.0000.2130.0600.0930.0000.2580.1650.2020.0000.0320.0000.2091.0000.2010.0000.2400.1900.0000.3311.0000.2490.2570.0000.1380.2180.2260.169
Violation Points - 170.0000.3450.0000.0000.0000.0000.1810.4730.1450.0000.0000.2680.3860.1710.2011.0000.2840.5580.4330.0000.0000.0000.4290.4190.3170.2800.3510.4190.241
Violation Points - 180.0000.0000.0000.4540.0000.0000.0870.2450.2640.2720.0570.3950.0570.1440.0000.2841.0000.3810.2560.6340.8940.0000.3430.4100.3510.2760.0000.1550.712
Violation Points - 190.0000.1711.0000.0000.0000.0000.1910.3930.1920.0000.0000.3140.0000.5400.2400.5580.3811.0000.2850.0500.6160.0000.5030.2170.2330.4420.3170.2850.230
Violation Points - 20.0740.2270.0310.0420.0390.0810.0610.2550.2170.1790.1880.2080.1980.1820.1900.4330.2560.2851.0000.8940.5001.0000.2410.1800.1550.1520.1520.1690.199
Violation Points - 200.0000.0001.0000.0001.0000.8940.0000.6710.0000.0000.0000.0000.0000.0000.0000.0000.6340.0500.8941.0000.8940.0000.6340.8940.8940.0000.4900.0000.000
Violation Points - 210.0000.0001.0000.0001.0000.5000.0000.3950.3950.0000.0000.3160.0000.0000.3310.0000.8940.6160.5000.8941.0000.0000.8940.5000.5000.0000.7420.0000.000
Violation Points - 220.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0000.0001.0000.0000.0000.0001.0000.0000.0001.0000.0001.0000.0000.0000.0000.0000.000
Violation Points - 30.0550.2500.0090.0630.0170.0700.0560.1380.1770.1900.1590.2590.2800.2640.2490.4290.3430.5030.2410.6340.8940.0001.0000.2330.1560.1550.1580.1780.151
Violation Points - 40.0560.2790.0000.0290.0000.0490.0550.1270.1480.1630.1600.2690.1310.1570.2570.4190.4100.2170.1800.8940.5001.0000.2331.0000.2170.1250.1320.1550.186
Violation Points - 50.0300.2150.0230.0000.0320.0220.0530.1520.1530.1610.1760.2810.2320.1710.0000.3170.3510.2330.1550.8940.5000.0000.1560.2171.0000.1770.0970.1220.149
Violation Points - 60.0690.1630.0460.0050.0000.0490.0650.1490.1150.0780.1240.1670.2120.2610.1380.2800.2760.4420.1520.0000.0000.0000.1550.1250.1771.0000.1500.1080.096
Violation Points - 70.0810.1800.0320.0000.0000.0470.0000.1760.0880.0590.1170.1760.2040.1440.2180.3510.0000.3170.1520.4900.7420.0000.1580.1320.0970.1501.0000.1810.113
Violation Points - 80.1110.1680.0580.0320.0000.0580.0400.1730.1070.0350.1130.1530.2250.2270.2260.4190.1550.2850.1690.0000.0000.0000.1780.1550.1220.1080.1811.0000.153
Violation Points - 90.0610.0980.0680.0150.0360.0520.0610.2030.1510.1170.0540.1410.1810.1940.1690.2410.7120.2300.1990.0000.0000.0000.1510.1860.1490.0960.1130.1531.000

Missing values

2025-04-14T23:23:32.035056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-14T23:23:32.983258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-04-14T23:23:36.067182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Restaurant NameInspection TypeInspection DateInspection ScoreStreet NumberStreet NameStreet DirectionStreet TypeStreet UnitStreet AddressZip CodeViolation Description - 1Violation Points - 1Violation Detail - 1Violation Memo - 1Violation Description - 2Violation Points - 2Violation Detail - 2Violation Memo - 2Violation Description - 3Violation Points - 3Violation Detail - 3Violation Memo - 3Violation Description - 4Violation Points - 4Violation Detail - 4Violation Memo - 4Violation Description - 5Violation Points - 5Violation Detail - 5Violation Memo - 5Violation Description - 6Violation Points - 6Violation Detail - 6Violation Memo - 6Violation Description - 7Violation Points - 7Violation Detail - 7Violation Memo - 7Violation Description - 8Violation Points - 8Violation Detail - 8Violation Memo - 8Violation Description - 9Violation Points - 9Violation Detail - 9Violation Memo - 9Violation Description - 10Violation Points - 10Violation Detail - 10Violation Memo - 10Violation Description - 11Violation Points - 11Violation Detail - 11Violation Memo - 11Violation Description - 12Violation Points - 12Violation Detail - 12Violation Memo - 12Violation Description - 13Violation Points - 13Violation Detail - 13Violation Memo - 13Violation Description - 14Violation Points - 14Violation Detail - 14Violation Memo - 14Violation Description - 15Violation Points - 15Violation Detail - 15Violation Memo - 15Violation Description - 16Violation Points - 16Violation Detail - 16Violation Memo - 16Violation Description - 17Violation Points - 17Violation Detail - 17Violation Memo - 17Violation Description - 18Violation Points - 18Violation Detail - 18Violation Memo - 18Violation Description - 19Violation Points - 19Violation Detail - 19Violation Memo - 19Violation Description - 20Violation Points - 20Violation Detail - 20Violation Memo - 20Violation Description - 21Violation Points - 21Violation Detail - 21Violation Memo - 21Violation Description - 22Violation Points - 22Violation Detail - 22Violation Memo - 22Violation Description - 23Violation Points - 23Violation Detail - 23Violation Memo - 23Violation Description - 24Violation Points - 24Violation Detail - 24Violation Memo - 24Violation Description - 25Violation Points - 25Violation Detail - 25Violation Memo - 25Inspection MonthInspection YearLat Long Location
0BLUE'S PALACE IIRoutine2023-08-18973100GRANDNaNAVENaN3100 GRAND AVE75215*10 Clean Sight and Touch3.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. Equipment, food-contact surfaces, non-food contact surfaces and utensils. (1) Equipment food-contact surfaces and utensils shall be clean to sight and touch.CLEAN INSIDE OF ICE MACHINENaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNAug 2023FY20233100 GRAND AVE
1JFE SUSHI K-511Routine2023-03-0210010677NORTHWESTEHWY#30010677 E NORTHWEST HWY #30075238NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMar 2023FY202310677 E NORTHWEST HWY #300\n(32.86516, -96.70169)
2DL MACK'S PRESTONRoutine2023-07-129710720PRESTONNaNRD#110110720 PRESTON RD #110175230*24 Food Labeling- with common name of the food2.0228.79 Food. Labeling. (a) Food labels. (2) Label information shall include: (A) the common name of the food, or absent a common name, an adequately descriptive identity statement;label squeeze bottles*42 Dirty nonfood contact surfaces1.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.clean bottom of RIFNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJul 2023FY202310720 PRESTON RD #1101
3THE POTTER'S HOUSE YOUTH ADDITIONRoutine2023-06-301006777KIESTWBLVDNaN6777 W KIEST BLVD75211NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJun 2023FY20236777 W KIEST BLVD
4MCDONALDS #4777Routine2023-07-12991000COMMERCENaNSTNaN1000 COMMERCE ST75202*45 Drying Mops-air dry1.0228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (f) Drying mops. After use, mops shall be placed in a position that allows them to air-dry without soiling walls, equipment, or supplies.hang mops when not in useNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJul 2023FY20231000 COMMERCE ST
5MEADOWSTONE PLACERoutine2023-03-0210010410STONE CANYONNaNNaNNaN10410 STONE CANYON75230NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMar 2023FY202310410 STONE CANYON\n(32.88812, -96.77511)
6AVANTI RISTORANTIRoutine2023-06-16992720MCKINNEYNaNAVENaN2720 MCKINNEY AVE75204*39 Store equipment & utensils in a clean, dry place1.0228.124 Equipment, Utensils, and Linens. Storage. (a) Equipment, utensils, linens, and single-service and single-use articles. (1) Except as specified in paragraph (4) of this subsection, cleaned equipment and utensils, laundered linens, and single-service and single-use articles shall be stored: (A) in a clean, dry location;ice scoopNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJun 2023FY20232720 MCKINNEY AVE\n(41.747200008, -71.140674982)
7WHOLE FOODS MARKET (BAKERY)Routine2023-12-121008190PARKNaNLN#3518190 PARK LN #35175231NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNDec 2023FY20248190 PARK LN #351
8THE PAVILLION CLUBRoutine2023-04-0996325CENTREWSTNaN325 W CENTRE ST75208*31 Handwashing lavatory - used for other purpose2.0228.149 Water, Plumbing, and Waste. Plumbing, operation and maintenance. (a) Using a handwashing facility. (2) A handwashing facility may not be used for purposes other than handwashing.do not use hand sink as dump sink*29 Sanitizing solutions, testing devices2.0228.108 Equipment, Utensils, and Linens. Utensils, temperature measuring devices, and testing devices. (e) Sanitizing solutions, testing device. A test kit or other device that accurately measures the concentration in mg/L of sanitizing solutions shall be provided.provide chemical test strips to check the sanitizerNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNApr 2023FY2023325 W CENTRE ST
9FIRST QUARTER BAR & GRILLRoutine2023-12-18998008HERBKELLEHERNaNWAYC22168008 HERBKELLEHER WAY STE. C221675235*42 Dirty nonfood contact surfaces1.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.Clean dirty floors (debris & water on floor), RIC/RIF gasketsNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNDec 2023FY20248008 HERBKELLEHER WAY STE. C2216
Restaurant NameInspection TypeInspection DateInspection ScoreStreet NumberStreet NameStreet DirectionStreet TypeStreet UnitStreet AddressZip CodeViolation Description - 1Violation Points - 1Violation Detail - 1Violation Memo - 1Violation Description - 2Violation Points - 2Violation Detail - 2Violation Memo - 2Violation Description - 3Violation Points - 3Violation Detail - 3Violation Memo - 3Violation Description - 4Violation Points - 4Violation Detail - 4Violation Memo - 4Violation Description - 5Violation Points - 5Violation Detail - 5Violation Memo - 5Violation Description - 6Violation Points - 6Violation Detail - 6Violation Memo - 6Violation Description - 7Violation Points - 7Violation Detail - 7Violation Memo - 7Violation Description - 8Violation Points - 8Violation Detail - 8Violation Memo - 8Violation Description - 9Violation Points - 9Violation Detail - 9Violation Memo - 9Violation Description - 10Violation Points - 10Violation Detail - 10Violation Memo - 10Violation Description - 11Violation Points - 11Violation Detail - 11Violation Memo - 11Violation Description - 12Violation Points - 12Violation Detail - 12Violation Memo - 12Violation Description - 13Violation Points - 13Violation Detail - 13Violation Memo - 13Violation Description - 14Violation Points - 14Violation Detail - 14Violation Memo - 14Violation Description - 15Violation Points - 15Violation Detail - 15Violation Memo - 15Violation Description - 16Violation Points - 16Violation Detail - 16Violation Memo - 16Violation Description - 17Violation Points - 17Violation Detail - 17Violation Memo - 17Violation Description - 18Violation Points - 18Violation Detail - 18Violation Memo - 18Violation Description - 19Violation Points - 19Violation Detail - 19Violation Memo - 19Violation Description - 20Violation Points - 20Violation Detail - 20Violation Memo - 20Violation Description - 21Violation Points - 21Violation Detail - 21Violation Memo - 21Violation Description - 22Violation Points - 22Violation Detail - 22Violation Memo - 22Violation Description - 23Violation Points - 23Violation Detail - 23Violation Memo - 23Violation Description - 24Violation Points - 24Violation Detail - 24Violation Memo - 24Violation Description - 25Violation Points - 25Violation Detail - 25Violation Memo - 25Inspection MonthInspection YearLat Long Location
10666T BAR M RAQUET CLUBRoutine2024-01-29906060DILBECKNaNLNNaN6060 DILBECK LN75240*22 Accredited food handler certificate - 60 days2.0õ228.33. Certified Food Protection Manager and Food Handler Requirements (d) Except in a temporary food establishment and the certified food manager, all food employees shall successfully complete an accredited food handler training course, within 60 days of employment.Provide up-to-date Food Handler Certificates*32 Equipment & Utensils smooth easily cleanable2.0228.101 Equipment, Utensils, and Linens. Multiuse materials. (a) Characteristics. Materials that are used in the construction of utensils and food-contact surfaces of equipment may not allow the migration of deleterious substances or impart colors, odors, or tastes to food and under normal use conditions shall be: (4) finished to have a smooth, easily cleanable surface; andReplace rusted WIC shelves*37 Food protected from cross contamination by storing the food in packages, covered containers, or1.0228.66 Food. Preventing food and ingredient contamination. (a) Packaged and unpackaged food - separation, packaging, and segregation. (1) Food shall be protected from cross contamination by: (D) except as specified in õ228.75(e)(2)(B) of this title and paragraph (2) of this subsection, storing the food in packages, covered containers, or wrappings;Cover all food in pantry and raw beef patties in freezer*39 Store all equipment & utensil covered or inverted1.0228.124 Equipment, Utensils, and Linens. Storage. (a) Equipment, utensils, linens, and single-service and single-use articles. (2) Clean equipment and utensils shall be stored as specified under paragraph (1) of this subsection and shall be stored: (B) covered or inverted.Invert all plates*45 Premises shall be maintained in good repair1.0228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (a) Repairing. The physical facilities shall be maintained in good repair.Replace water damaged ceiling tiles*10 Clean Sight and Touch3.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. Equipment, food-contact surfaces, non-food contact surfaces and utensils. (1) Equipment food-contact surfaces and utensils shall be clean to sight and touch.Clean/replace rusted panel on ice machinesNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJan 2024FY20246060 DILBECK LN
10667LITTLE VEE'S BAR-BE-QUE & MORERoutine2024-01-24747620GREAT TRINITY FORESTNaNWAYNaN7620 GREAT TRINITY FOREST WAY75217*09 Food protected cross contamination separating types of raw animal food storage, preparation, hol3.0228.66 Food. Preventing food and ingredient contamination. (a) Packaged and unpackaged food - separation, packaging, and segregation. (1) Food shall be protected from cross contamination by: (B) except when combined as ingredients, separating types of raw animal foods from each other such as beef, fish, lamb, pork, and poultry during storage, preparation, holding, and display by: (i) using separate equipment for each type; orobserved eggs on top shelves above tcs food*19 Water & Plumbing in good repair- per code3.0228.149 Water, Plumbing, and Waste. Plumbing, operation and maintenance. (e) System maintained in good repair. A plumbing system shall be: (1) repaired according to the Plumbing Code; andobserved leaking water from faucet*21 RFSM - Not On Site2.0Sec. 17-2.2(c)(1)(D) (c) Registered food service managers. (1) Registered food service managers required. (D) A food establishment shall have one registered food service manager employed and present in the establishment during all hours of operation, except that a registered food service manager serving multiple food establishments as authorized by Section 17-2.2(c)(1)(C) must only be present in the building in which the food establishment is located during all hours of operation.rfsm missing on site*28 Date marking combined ingredients for RTE/ TCS food2.0228.75 Food. Time and temperature control. (g) Ready-to-eat, TCS food, date marking. (3) A refrigerated, ready-to-eat TCS food ingredient or a portion of a refrigerated, ready-to-eat, TCS food that is subsequently combined with additional ingredients or portions of food shall retain the date marking of the earliest-prepared or first-prepared ingredientproperly date mark rte and tcs food*29 Sanitizing solutions, testing devices2.0228.108 Equipment, Utensils, and Linens. Utensils, temperature measuring devices, and testing devices. (e) Sanitizing solutions, testing device. A test kit or other device that accurately measures the concentration in mg/L of sanitizing solutions shall be provided.missing test strips*31 No soap at handsink2.0228.175 Physical Facilities. Handwashing Sinks. (b) Handwashing cleanser, availability. Each handwashing lavatory or group of two adjacent lavatories shall be provided with a supply of hand cleaning liquid, powder, or bar soap.hand soap and paper towel missing*32 Smooth Contact Surfaces2.0228.104 Equipment, Utensils, and Linens. Cleanability. (a) Food-contact surfaces. Multi use food-contact surfaces shall be: (1) smooth;resurface the chop board or replace it*35 Jewelry Prohibition1.0228.40 Management and Personnel. Jewelry Prohibition. Except for a plain ring such as a wedding band, while preparing food, food employees may not wear jewelry including medical information jewelry on their arms and hands.observed employees wearing neck chains, need to be removed while cooking or handling food*41 Food Labeling - Bulk Food w/ Card or Sign1.0228.79 Food. Labeling. (a) Food labels. (3) Bulk food that is available for consumer self-dispensing shall be prominently labeled with the following information in plain view of the consumer: (B) a card, sign, or other method of notification that includes the information specified in paragraph (2)(A), (B), and (F) of this subsection.no labeling on bulk food container*42 Dirty nonfood contact surfaces1.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.clean inside the hot hold oven, clean the shelves*46 Toilet tissue, availability1.0228.176 Physical Facilities. Toilets and urinals. (b) Toilet tissue, availability. A supply of toilet tissue shall be available at each toilet.provide paper towels on restroom*22 Accredited food handler certificate - 60 days2.0õ228.33. Certified Food Protection Manager and Food Handler Requirements (d) Except in a temporary food establishment and the certified food manager, all food employees shall successfully complete an accredited food handler training course, within 60 days of employment.food handler card missing*20 Grease Trap Tickets3.0Ch.19-126.5(c)) A producer shall sign the manifest from the transporter when a load is picked up by the transporter and shall keep a copy of all trip tickets at the producer#s business office for three years. The director may inspect these records at any reasonable time.grease trap tickets needs to be on site (latest)*34 Pest control-routine inspections for1.0228.186 Physical Facilities. Premises, buildings, systems, rooms, fixtures, equipment, devices, and materials. (k) Controlling pests. The presence of insects, rodents, and other pests shall be controlled to minimize their presence within the physical facility and its contents, and on the contiguous land or property under the control of the permit holder by: (2) routinely inspecting the premises for evidence of pests;missing pest control receiptNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJan 2024FY20247620 GREAT TRINITY FOREST WAY\n(32.712226986, -96.691076037)
10668TORTAS Y TACOS EL RANCHITO #1 (TO GO)Routine2024-01-19918017LAKE JUNENaNRD#F8017 LAKE JUNE RD #F75217*21 RFSM - Not On Site2.0Sec. 17-2.2(c)(1)(D) (c) Registered food service managers. (1) Registered food service managers required. (D) A food establishment shall have one registered food service manager employed and present in the establishment during all hours of operation, except that a registered food service manager serving multiple food establishments as authorized by Section 17-2.2(c)(1)(C) must only be present in the building in which the food establishment is located during all hours of operation.food manager certificate expired*18 Toxic items labeling-non original container3.0228.202 Poisonous or Toxic Materials. Working containers, common name. Working containers used for storing poisonous or toxic materials such as cleaners and sanitizers taken from bulk supplies shall be clearly and individually identified with the common name of the material.provide label for chemical spray bottle and sanitizer bucket*39 Utensils, single serve items 6 inches off - floor1.0228.124 Equipment, Utensils, and Linens. Storage. (a) Equipment, utensils, linens, and single-service and single-use articles. (1) Except as specified in paragraph (4) of this subsection, cleaned equipment and utensils, laundered linens, and single-service and single-use articles shall be stored: (C) at least 15 centimeters (6 inches) above the floor.store utensils 6 inches off floor*43 Ventilation hood-prevent grease dripping1.0228.106 Equipment, Utensils, and Linens. Functionality of equipment. (a) Ventilation hood systems, drip prevention. Exhaust ventilation hood systems in food preparation and warewashing areas including components such as hoods, fans, guards, and ducting shall be designed to prevent grease or condensation from draining or dripping onto food, equipment, utensils, linens, and single-service and single-use articles.catch grease bucket*32 Damaged Equipment2.0228.104 Equipment, Utensils, and Linens. Cleanability. (a) Food-contact surfaces. Multi use food-contact surfaces shall be: (2) free of breaks, open seams, cracks, chips, inclusions, pits, and similar imperfections;freezer-rusty exterior, cooler on front is damaged remove or repairNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJan 2024FY20248017 LAKE JUNE RD #F\n(28.87547064, -81.512021105)
10669ORIGINAL CHOP SHOPRoutine2024-02-019611700PRESTONNaNRD#61211700 PRESTON RD #61275230*37 Storing the food at least 15 cm (6 inches) above the floor1.0228.69 Food. Preventing contamination from the premises. (a) Food Storage. (1) Except as specified in paragraphs (2) and (3) of this subsection, food shall be protected from contamination by storing the food: (C) at least 15 centimeters (6 inches) above the floor.store food 6 inches off the floor (carrots in the walk in cooler)*42 Nonfood-contact surfaces material1.0228.101 Equipment, Utensils, and Linens. Multiuse materials. (i) Nonfood-contact surfaces. Nonfood-contact surfaces of equipment that are exposed to splash, spillage, or other food soiling or that require frequent cleaning shall be constructed of a corrosion-resistant, nonabsorbent, and smooth material.clean interior of the reach in cooler/freezer*28 Date marking > 24 hrs,on site,temp 41F2.0228.75 Food. Time and temperature control. (g) Ready-to-eat, TCS food, date marking. (2) Except as specified in paragraphs (5) - (7) of this subsection, refrigerated, ready-to-eat, time/temperature controlled for safety food prepared and packaged by a food processing plant shall be clearly marked, at the time the original container is opened in a food establishment and held at a temperature of 41 degrees Fahrenheit (5 degrees Celsius) or less if the food is held for more than 24 hours, to indicate the date or day by which the food shall be consumed on the premises, sold, or discarded, based on the temperature and time combinations specified in paragraph (1) of this subsection: (A) the day the original container is opened in the food establishment shall be counted as day 1; andDiscard food in the walk in cooler by use by dateNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFeb 2024FY202411700 PRESTON RD #612
10670PAPA JOHNS PIZZARoutine2024-01-12951127BECKLEYNAVENaN1127 N BECKLEY AVE75203*10 Clean Sight and Touch3.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. Equipment, food-contact surfaces, non-food contact surfaces and utensils. (1) Equipment food-contact surfaces and utensils shall be clean to sight and touch.Can opener blade observed w/ residue*37 Preventing contamination from other sources. Miscellaneous sources of Contamination1.0228.70 Food. Preventing contamination by consumers. (e) Preventing contamination from other sources. Miscellaneous sources of Contamination. Food shall be protected from contamination that may result from a factor or source not specified in õõ228.65 - 228.70 of this title.Due to residue on blade any other cans opened with can opener exposed to cross contamination*45Physical Facilities Floors,Walls,Ceilings1.0228.173 Physical Facilities. Floors, walls, and ceilings. (a) Cleanability. Except as specified under subsection (d) of this section, and except for antislip floor coverings or applications that may be used for safety reasons, the floors, floor coverings, walls, wall coverings, and ceilings shall be designed, constructed, and installed so they are smooth and easily cleanable,Fix broken base boards by prep coolerNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJan 2024FY20241127 N BECKLEY AVE
10671WHOLE FOODS MARKET/BAKERYRoutine2024-02-09952118ABRAMSNaNRDNaN2118 ABRAMS RD75214*19 Water & Plumbing in good repair- per code3.0228.149 Water, Plumbing, and Waste. Plumbing, operation and maintenance. (e) System maintained in good repair. A plumbing system shall be: (1) repaired according to the Plumbing Code; andfaucet leaking at prep sink*37 Storing the food at least 15 cm (6 inches) above the floor1.0228.69 Food. Preventing contamination from the premises. (a) Food Storage. (1) Except as specified in paragraphs (2) and (3) of this subsection, food shall be protected from contamination by storing the food: (C) at least 15 centimeters (6 inches) above the floor.bag of sugar on floor- must be 6 inches or more off floor*42 Dirty nonfood contact surfaces1.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.clean off display case doors/ tracks, bunkersNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFeb 2024FY20242118 ABRAMS RD
10672FIESTA MART SEAFOODRoutine2024-02-09905334ROSSNaNAVENaN5334 ROSS AVE75204*21 RFSM - Not On Site2.0Sec. 17-2.2(c)(1)(D) (c) Registered food service managers. (1) Registered food service managers required. (D) A food establishment shall have one registered food service manager employed and present in the establishment during all hours of operation, except that a registered food service manager serving multiple food establishments as authorized by Section 17-2.2(c)(1)(C) must only be present in the building in which the food establishment is located during all hours of operation.RFSM not on site*32 Maintain in Good Repair2.0228.223 REQUIREMENTS APPLICABLE TO CERTAIN ESTABLISHMENTS Bed and Breakfast . (h) Equipment and utensil design and construction. All equipment and utensils shall be constructed of safe materials and maintained in good repair.cutting board needs to be resurfaced from any damaged surfaces*36 Cloths in-use for wiping between uses stored1.0228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (d) Wiping cloths, use limitation. (2) cloths in-use for wiping counters and other equipment surfaces shall be: (A) held between uses in a chemical sanitizer solution at a concentration specified in õ228.111(n) of this title; andwiping cloths need ti be in bucket between usages*19 Water & Plumbing in good repair- per code3.0228.149 Water, Plumbing, and Waste. Plumbing, operation and maintenance. (e) System maintained in good repair. A plumbing system shall be: (1) repaired according to the Plumbing Code; and3 comp sink is leaking from under side , needs to be repaired*39 Equipment-doors, seal hinges adjusted/intact1.0228.111 Equipment, Utensils, and Linens. Equipment, maintenance and operation. (a) Good repair and proper adjustment. (2) Equipment components such as doors, seals, hinges, fasteners, and kick plates shall be kept intact, tight, and adjusted in accordance with manufacturer's specifications.seal on the WIF needs to be repaired*47 Other Violations1.0NaNFood permit not displayedNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFeb 2024FY20245334 ROSS AVE
10673EL RIO GRANDE LATIN MARKET #10 (PRODUCE)Routine2024-02-08973035BUCKNERNBLVDNaN3035 N BUCKNER BLVD75228*31 Individual, disposable towels2.0228.175 Physical Facilities. Handwashing Sinks. (c) Hand drying provision. Each handwashing lavatory or group of adjacent lavatories shall be provided with: (1) individual, disposable towels;no paper towels at back hand sink (WIC/ prep area)*42 Dirty nonfood contact surfaces1.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.clean along bottom of display bunkers/ edgesNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFeb 2024FY20243035 N BUCKNER BLVD
10674EL CHAROLAZO COMIDA MEXICANA CON SABORRoutine2024-02-098211200HARRY HINESNaNBLVD#WXZ11200 HARRY HINES BLVD #WXZ75229*09 Food protected cross contamination arrange each type food in equipment so cross is prevented3.0228.66 Food. Preventing food and ingredient contamination. (a) Packaged and unpackaged food - separation, packaging, and segregation. (1) Food shall be protected from cross contamination by: (B) except when combined as ingredients, separating types of raw animal foods from each other such as beef, fish, lamb, pork, and poultry during storage, preparation, holding, and display by: (ii) arranging each type of food in equipment so that cross contamination of one type with another is prevented; andobserved eggs stored above produce in ric*21 RFSM - Not On Site2.0Sec. 17-2.2(c)(1)(D) (c) Registered food service managers. (1) Registered food service managers required. (D) A food establishment shall have one registered food service manager employed and present in the establishment during all hours of operation, except that a registered food service manager serving multiple food establishments as authorized by Section 17-2.2(c)(1)(C) must only be present in the building in which the food establishment is located during all hours of operation.food manager was not onsite*29 Sanitizing solutions, testing devices2.0228.108 Equipment, Utensils, and Linens. Utensils, temperature measuring devices, and testing devices. (e) Sanitizing solutions, testing device. A test kit or other device that accurately measures the concentration in mg/L of sanitizing solutions shall be provided.missing test strips*31 Heated air hand drying device2.0228.175 Physical Facilities. Handwashing Sinks. (c) Hand drying provision. Each handwashing lavatory or group of adjacent lavatories shall be provided with: (3) a heated-air hand drying device.missing drying towel in both hand sinks*36 Cloths in-use for wiping between uses stored1.0228.68 Food. Preventing Contamination From Equipment, Utensils, and Linens. (d) Wiping cloths, use limitation. (2) cloths in-use for wiping counters and other equipment surfaces shall be: (A) held between uses in a chemical sanitizer solution at a concentration specified in õ228.111(n) of this title; andneed to store mop cloths in bucket*43 Light - 50 foot : Food and utensils area1.0228.177 Physical Facilities. Lighting, intensity. The light intensity shall be: (3) at least 540 lux (50 foot candles) at a surface where a food employee is working with food or working with utensils or equipment such as knives, slicers, grinders, or saws where employee safety is a factor.vent light is out*45Floor, wall, ceiling - Exposed material1.0(c) Floors, walls, and ceilings. (1) A food establishment containing a food handling area, food processing area, food preparation area, food storage area, equipment or utensil washing area, walk-in refrigerating unit, dressing room, locker room, toilet room, or vestibule shall: (C) prevent exposed construction in these areas, including but not limited to the exposure of pipes, conduits, ductwork, studs, joists, and rafters;need to repair ceiling gaps*15 Bare hands contact with ready-to-eat foods3.0228.65 Food. Preventing contamination by employees. (a) Preventing contamination from hands. (2) Except when washing fruits and vegetables as specified in õ228.66(e) of this title or as specified in paragraphs (4) and (5) of this subsection, food employees may not contact exposed, ready-to-eat food with their bare hands and shall use suitable utensils such as deli tissue, spatulas, tongs, single-use gloves, or dispensing equipment.need to wear gloves when handling cooked tortila*19 Backflow Prevention. The plumbing system shall preclude backflow of a solid, liquid, or gas cont3.0228.273 PRIVATE WATER SYSTEMS Backflow Prevention The plumbing system shall preclude backflow of a solid, liquid, or gas contaminant into the water supply system at each point of use, including on a hose bib, by: (2) installing an approved backflow prevention device that meets the American Society of Sanitary Engineering (ASSE) standards for construction, installation, maintenance, inspection, and testing for that specific application and type of device.need to repair leaking mop sinkNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNFeb 2024FY202411200 HARRY HINES BLVD #WXZ
10675PARSONS HOUSE PRESTON HOLLOWRoutine2024-01-22924205NORTHWESTWHWYNaN4205 W NORTHWEST HWY75220*09 Raw ready to eat - Food protected from cross contamination by separating, storage, preparation,3.0228.66 Food. Preventing food and ingredient contamination. (a) Packaged and unpackaged food - separation, packaging, and segregation. (1) Food shall be protected from cross contamination by: (A) except as specified in subparagraph (A)(iii) of this paragraph,separating raw animal foods during storage, preparation, holding, and display from: (i) raw ready-to-eat food including other raw animal food such as fish for sushi or molluscan shellfish, or other raw ready-to-eat food such as vegetables; andcannot store raw food (bacon, eggs) above ready to eat food (veggies)*42 Nonfood-contact surfaces material1.0228.101 Equipment, Utensils, and Linens. Multiuse materials. (i) Nonfood-contact surfaces. Nonfood-contact surfaces of equipment that are exposed to splash, spillage, or other food soiling or that require frequent cleaning shall be constructed of a corrosion-resistant, nonabsorbent, and smooth material.clean the interior of the reach in cooler*16 Substitued pasteurized eggs/broken eggs....3.0228.82 Food. Additional safeguards, requirements for food establishments serving highly susceptible populations. Pasteurized foods and prohibited food. In a food establishment that serves a highly susceptible population: . (2) Pasteurized eggs, egg products. Pasteurized shell eggs or pasteurized liquid, frozen, or dry eggs or egg products shall be substituted for raw shell eggs in the preparation of: (B) except as specified in paragraph (6) of this subsection, recipes in which more than one egg is broken and the eggs are combined;provide pasteurized eggs (shelled eggs not pasteurized)*37 Storing the food at least 15 cm (6 inches) above the floor1.0228.69 Food. Preventing contamination from the premises. (a) Food Storage. (1) Except as specified in paragraphs (2) and (3) of this subsection, food shall be protected from contamination by storing the food: (C) at least 15 centimeters (6 inches) above the floor.store food 6 inches off the ground (food on floor in the walk in freezer)NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJan 2024FY20244205 W NORTHWEST HWY

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13MCDONALDSRoutine2023-03-30994223ILLINOISWAVENaN4223 W ILLINOIS AVE75211*39 Soda nozzles and ice bin clean as specified1.0228.114 Equipment, Utensils, and Linens. Frequency of cleaning. (a) Equipment food-contact surfaces and utensils. (5) Except when dry cleaning methods are used as specified in õ228.115(a) of this title, surfaces of utensils and equipment contacting food that is not time/temperature control for safety shall be cleaned: (D) in equipment such as ice bins and beverage dispensing nozzles and enclosed components of equipment such as ice makers, cooking oil storage tanks and distribution lines, beverage and syrup dispensing lines or tubes, coffee bean grinders, and water vending equipment: (i) at a frequency specified by the manufacturerOBSERVED RUST AROUND SCREW IN ICE MACHINE, COLLECTING CONDENSATION. USE MATERIAL THAT DOES NOT RUST OR IS MORE RESISTED TO RUSTING, CLEAN AROUND SCREW.NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMar 2023FY20234223 W ILLINOIS AVE\n(32.72093, -96.88957)3
0AMERICAN FOOD VENDING SERVICES @ TI DMOS (CALL 214-789-1656)Routine2023-04-2610013353TINaNBLVDNaN13353 TI BLVD75243NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNApr 2023FY202313353 TI BLVD2
1BAYLOR UNIVERSITY MED CTR PHYSICIANSRoutine2023-08-161003500GASTONNaNAVENaN3500 GASTON AVE75246NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNAug 2023FY20233500 GASTON AVE2
2BISHOP DUNNE HIGH STADIUMRoutine2023-11-15993900RUGGEDNaNDRNaN3900 RUGGED DR75224*42 Dirty nonfood contact surfaces1.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. (3) Nonfood-contact surfaces of equipment shall be kept free of an accumulation of dust, dirt, food residue, and other debris.Ceiling fan blades shall be clean to sightNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNov 2023FY20243900 RUGGED DR2
3FAITH FAMILY ACADEMYRoutine2023-11-16100300KIESTWBLVDNaN300 W KIEST BLVD75224NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNov 2023FY2024300 W KIEST BLVD2
4FOODA AT SOUTHWEST AIRLINES (CAFETERIA SEATING AREA)Routine2024-01-31972195RESEARCHNaNROWNaN2195 RESEARCH ROW75235*24 Food Labeling- with common name of the food2.0228.79 Food. Labeling. (a) Food labels. (2) Label information shall include: (A) the common name of the food, or absent a common name, an adequately descriptive identity statement;Label squeeze bottles with name of food*35 Hair Restraints effective1.0228.43 Management and Personnel. Hair restraints. (a) Except as provided in subsection (b) of this section, food employees shall wear hair restraints such as hats, hair coverings or nets, beard restraints, and clothing that covers body hair, that are designed and worn to effectively keep their hair from contacting exposed food; clean equipment, utensils, and linens; and unwrapped single-service and single-use articles.Provide hair net to be effectiveNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJan 2024FY20242195 RESEARCH ROW2
5GOLDEN CHICKRoutine2024-01-039410443CENTRALNEXPWNaN10443 N CENTRAL EXPW75231*03 <<<HOT HOLD (135øF)>>>3.0NaNNaN*10 Clean Sight and Touch3.0228.113 Equipment, Utensils, and Linens. Cleaning of equipment and utensils. Equipment, food-contact surfaces, non-food contact surfaces and utensils. (1) Equipment food-contact surfaces and utensils shall be clean to sight and touch.NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJan 2024FY202410443 N CENTRAL EXPW2
6HALAL GUYSRoutine2023-05-11985444LEMMONNaNAVENaN5444 LEMMON AVE75209*21 RFSM - Not On Site2.0Sec. 17-2.2(c)(1)(D) (c) Registered food service managers. (1) Registered food service managers required. (D) A food establishment shall have one registered food service manager employed and present in the establishment during all hours of operation, except that a registered food service manager serving multiple food establishments as authorized by Section 17-2.2(c)(1)(C) must only be present in the building in which the food establishment is located during all hours of operation.NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNMay 2023FY20235444 LEMMON AVE2
7LA SUPER ECONOMICA #6 BAKERYRoutine2023-08-19962402GUS THOMASSONNaNRDNaN2402 GUS THOMASSON RD75228-3007*31 No soap at handsink2.0228.175 Physical Facilities. Handwashing Sinks. (b) Handwashing cleanser, availability. Each handwashing lavatory or group of two adjacent lavatories shall be provided with a supply of hand cleaning liquid, powder, or bar soap.STOCK HAND SINK WITH SOAP*39 Equipment and Utensils Storage1.0228.124 Equipment, Utensils, and Linens. Storage. (a) Equipment, utensils, linens, and single-service and single-use articles. (4) Items that are kept in closed packages may be stored less than 15 cm (6 inches) above the floor on dollies, pallets, racks, and skids that are designed as specified in õ228.106(v) of this title.DO NOT STORE UTENSILS (TONGS) BETWEEN DOORS AT PASTRY CASES*47 Other Violations1.0NaNLABEL 3 SINK WITH DIRECTIONS: WASH/ RINSE/ SANITIZENaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNAug 2023FY20232402 GUS THOMASSON RD\n(32.83398599, -96.674873986)2
8LEGACY MIDTOWN PARKRoutine2024-01-021008240MANDERVILLENaNLNNaN8240 MANDERVILLE LN75231NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNJan 2024FY20248240 MANDERVILLE LN2